Information processing system and information processing method

Abstract

To support the design of a measure by a measure policy in which action promotion to an object person and the restriction of a mounting environment are considered.SOLUTION: An information processing system holds measure policy information indicating a measure policy of a measure for promoting an action of a target person and an implementation condition required for a terminal to implement the measure based on the measure policy, acquires an implementation example of a measure distributed in the past corresponding to a designated target person and situation, and specifies a measure policy having a high action promotion level as a measure policy candidate based on a predetermined condition. The implementability of the measure policy candidate is evaluated on the basis of whether or not an implementation condition corresponding to the measure policy candidate in the measure policy information is satisfied in the acquired implementation example, and the measure policy candidate and the action promotion degree and implementability of the measure policy candidate are displayed.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing system and an information processing method. [Background technology]

[0002] JP 2023-182072 A (Patent Document 1) is a background technology in this technical field. This publication states that "a computer selects a specific intervention method from multiple intervention methods based on first characteristic information indicating the characteristics of an intervention target. The computer calculates an estimated characteristic change amount that represents the difference between the first characteristic information and second characteristic information indicating the characteristics of the intervention target after the specific intervention method has been applied. The computer searches for specific case data from case data that includes the intervention methods, characteristic information, and characteristic change amounts for each of multiple people. The specific case data includes a combination of characteristic information and characteristic change amount similar to the combination of the first characteristic information and estimated characteristic change amount, and the specific intervention method. The computer outputs information based on the specific case data" (see Abstract). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-182072 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology described in Patent Document 1 selects an intervention method for a target person from among multiple intervention methods, but does not take into account constraints on the implementation environment for implementing the intervention method, which makes it easy for the selected intervention method to become unusable due to implementation issues.

[0005] Therefore, one aspect of the present invention supports the design of measures based on a policy that takes into consideration the promotion of action for a target person and the constraints of the implementation environment. [Means for solving the problem]

[0006] In order to solve the above problem, one aspect of the present invention employs the following configuration: An information processing system includes a processor and a memory, and the memory stores policy information indicating a policy policy for a policy to encourage a target person to take action, implementation conditions required for a terminal owned by the target person in order for the policy policy to be implemented in the terminal, implementation examples of the policy that have been distributed in the past, target persons and situations of the policy in the implementation examples, and implementation example information indicating whether the terminal to which the policy in the implementation example was distributed satisfied each of the implementation conditions, and a behavior promotion degree of the policy based on the policy policy for the target person, and the processor stores: The system accepts the specification of a target person and a situation, obtains implementation examples corresponding to the specified target person and situation from the implementation example information, identifies the policy policy whose behavior promotion level is high based on specified conditions as a policy policy candidate, evaluates the implementability of the policy policy candidate based on whether the implementation conditions corresponding to the policy policy candidate in the policy policy information are satisfied in the obtained implementation example, and generates data for displaying a policy proposal screen including a display showing the policy policy candidate, the behavior promotion level, and the implementability of the policy policy candidate. [Effects of the Invention]

[0007] According to one aspect of the present invention, it is possible to support the design of measures based on a policy that takes into consideration the promotion of action for a target person and the constraints of the implementation environment.

[0008] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an example of the configuration of a policy design and distribution system according to a first embodiment. [Figure 2] FIG. 10 is a diagram illustrating an example of a data configuration of a policy plan table according to the first embodiment. [Figure 3] FIG. 10 is a diagram illustrating an example of a data configuration of an implementation example table according to the first embodiment. [Figure 4] FIG. 10 is a diagram illustrating an example of a data configuration of a policy distribution setting table according to the first embodiment. [Figure 5] FIG. 4 is a diagram illustrating an example of a data configuration of a project management table according to the first embodiment. [Figure 6] FIG. 2 is a diagram illustrating an example of a data configuration of a subject information table according to the first embodiment. [Figure 7] FIG. 4 is a diagram illustrating an example of a data configuration of a behavior table according to the first embodiment. [Figure 8] FIG. 2 is an explanatory diagram illustrating an example of an outline of processing by the policy design distribution system according to the first embodiment. [Figure 9] 10 is a flowchart showing an example of details of processing by the policy design and distribution system according to the first embodiment. [Figure 10] FIG. 10 is a diagram showing an example of a screen configuration of a measure proposal screen in the first embodiment. [Figure 11] FIG. 10 is a diagram illustrating an example of a screen configuration of a policy editing screen in the first embodiment. [Figure 12] FIG. 10 is a diagram showing an example of a screen configuration of a policy application effect display screen in the first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In this embodiment, the same components are generally designated by the same reference numerals, and repeated explanations will be omitted. It should be noted that this embodiment is merely an example for realizing the present invention, and does not limit the technical scope of the present invention. [Example]

[0011] Fig. 1 is a block diagram showing an example of the configuration of a policy design and distribution system. The policy design and distribution system 100 is a system used, for example, by a policy designer, and is connected to one or more terminals 200 via a network 300 such as the Internet. The policy design and distribution system 100 designs policies that intervene with the action promotion target person to encourage the action promotion target person to take a specific action (to change the behavior of the action promotion target person), and distributes the policies to the terminals 200. Hereinafter, such policies will also be simply referred to as "policies".

[0012] The policy design and distribution system 100 is configured by a computer having, for example, a CPU (Central Processing Unit) 101, an auxiliary storage device 102, a memory 103, an input device 104, a display device 105, and a communication device 106.

[0013] The CPU 101 includes a processor and executes programs stored in the memory 103. The memory 103 includes a ROM (Read Only Memory), which is a non-volatile storage element, and a RAM (Random Access Memory), which is a volatile storage element. The ROM stores unchanging programs (e.g., a BIOS (Basic Input / Output System)). The RAM is a high-speed, volatile storage element such as a DRAM (Dynamic Random Access Memory), and temporarily stores programs executed by the CPU 101 and data used when the programs are executed.

[0014] The auxiliary storage device 102 is a large-capacity, non-volatile storage device such as a magnetic storage device (HDD (Hard Disk Drive)) or a flash memory (SSD (Solid State Drive)), and stores programs to be executed by the CPU 101 and data to be used when the programs are executed. That is, the programs are read from the auxiliary storage device 102, loaded into the memory 103, and executed by the CPU 101.

[0015] The input device 104 is a device such as a keyboard or mouse that receives input from an operator. The display device 105 is a device such as a display device or printer that outputs the results of program execution in a format that can be viewed by the operator.

[0016] The communication device 106 is a network interface device that controls communication with other devices in accordance with a predetermined protocol, and may also include a serial interface such as a USB (Universal Serial Bus).

[0017] A part or all of the programs executed by the CPU 101 may be provided to the policy design and distribution system 100 from a removable medium (CD-ROM, flash memory, etc.) which is a non-transitory storage medium, or from an external computer equipped with a non-transitory storage device via the network 300, and may be stored in the non-volatile auxiliary storage device 102 which is a non-transitory storage medium. For this reason, the policy design and distribution system 100 should preferably have an interface for reading data from removable media.

[0018] The policy design and distribution system 100 is a computer system configured on a single physical computer or on multiple logically or physically configured computers, and may operate in separate threads on the same computer, or on a virtual computer constructed on multiple physical computer resources.

[0019] The CPU 101 includes, for example, an evaluation parameter generation unit 111, a behavior promotion evaluation unit 112, an implementation possibility evaluation unit 113, an implementation case acquisition unit 114, a policy content distribution unit 115, a policy editor UI generation unit 116, and an effect measurement unit 117, all of which are functional units.

[0020] The evaluation parameter generation unit 111 generates baseline parameters required for the behavior promotion level evaluation unit 112 to evaluate the behavior promotion level for a policy policy. The behavior promotion level evaluation unit 112 evaluates the behavior promotion level of a policy policy. The behavior promotion level of a policy policy is, for example, a policy that promotes the promotion of a certain behavior, and indicates the degree to which the behavior is promoted in the behavior promotion target when a policy based on the policy policy is implemented for the behavior promotion target (implemented in the terminal 200 used by the behavior promotion target). Hereinafter, the behavior promoted by the policy, i.e., the behavior that the behavior promotion target is desired to take, may also be referred to as a promotion behavior.

[0021] The implementation possibility evaluation unit 113 evaluates the implementability of a measure using the policy policy on the terminal 200 to which the policy policy is distributed. The implementation example acquisition unit 114 acquires implementation examples of the policy. The policy editor UI generation unit 116 displays a policy proposal screen (described later) showing the action promotion level and implementability of the policy policy and a policy editing screen for editing policy content on the display device 105, and determines the policy content to be distributed based on inputs on the policy proposal screen and the policy editing screen.

[0022] The policy content distribution unit 115 transmits the determined policy content to the terminal 200 used by the target person for behavior promotion to whom the policy content is to be distributed. The effect measurement unit 117 measures the effect of the distributed policy content (for example, the effect on whether the user (target person for behavior promotion) of the terminal 200 to which the policy content is distributed has taken the promotion behavior).

[0023] For example, the CPU 101 functions as an evaluation parameter generation unit 111 by operating in accordance with an evaluation parameter generation program loaded into the memory 103, and functions as a behavior promotion level evaluation unit 112 by operating in accordance with a behavior promotion level evaluation program loaded into the memory 103. The same applies to the other functional units included in the CPU 101 and their relationships with the programs.

[0024] Note that some or all of the functions of the functional units included in the CPU 101 may be realized by hardware such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array).

[0025] The auxiliary storage device 102 stores, for example, a policy direction table 121, a policy implementation example table 122, a policy distribution setting table 123, a project management table 124, a target person information table 125, and an action table 126.

[0026] The policy policy table 121 holds information about policy policies. The policy implementation example table 122 holds information about examples of policies implemented in the past (policy content distributed in the past). The policy distribution setting table 123 holds information about distribution settings of policy content that has been decided to be distributed.

[0027] The project management table 124 holds information showing a list of projects. Promotion actions are defined in the projects. The target person information table 125 holds information showing a list of action promotion targets. Hereinafter, action promotion targets may also be simply referred to as targets. The action table 126 holds information showing a list of promotion actions.

[0028] In addition, some or all of the information stored in the auxiliary storage device 102 may be stored in the memory 103, or in an external database connected to the policy design and distribution system 100 via the network 300.

[0029] In this embodiment, the information used by the policy design and distribution system 100 does not depend on the data structure and may be expressed in any data structure. For example, the information can be stored in a data structure appropriately selected from a table, a list, a database, or a queue.

[0030] The terminal 200 receives content indicating a measure from the measure design and distribution system 100 and displays the content. Depending on the type of content, the terminal 200 may accept input corresponding to the content, and may transmit information obtained by the input to the measure design and distribution system 100. The terminal 200 is used by each of the target persons for action promotion.

[0031] The terminal 200 is configured by a computer having, for example, a CPU 201, an auxiliary storage device 202, a memory 203, an input device 204, a display device 205, and a communication device 206. The terminal 200 is, for example, a computer such as a PC (Personal Computer), a smartphone, or a tablet.

[0032] Descriptions of the CPU 201, auxiliary storage device 202, memory 203, input device 204, display device 205, and communication device 206 as hardware will be omitted because they are the same as the descriptions of the CPU 101, auxiliary storage device 102, memory 103, input device 104, display device 105, and communication device 106 as hardware. Note that there may be a terminal 200 that does not have the input device 104, there may be a terminal 200 that does not have the display device 105, or there may be a terminal 200 that has other hardware.

[0033] 2 is a diagram showing an example of the data configuration of the policy policy table 121. The policy policy table 121 includes, for example, a policy policy column 1211, an explanation column 1212, a parameter column for behavior promotion level evaluation 1213, and a parameter column for implementability evaluation 1214. The policy policy column 1211 holds information indicating the policy of the policy. The explanation column 1212 holds information indicating an explanation of the policy policy.

[0034] The parameter for evaluating the promotion level of an action of a policy is stored in the parameter for evaluating the promotion level of an action of a policy. The parameter for evaluating the promotion level of an action of an action of a policy is defined by, for example, one or more feature quantities (N feature quantities in this embodiment) indicating the features of the policy.

[0035] The parameters for evaluating the level of behavior promotion include, for example, at least one of a nominal feature and an ordinal feature, and also include, for example, a feature related to the situation of the policy, a feature related to the target person for behavior promotion, and a feature related to the promotion behavior.

[0036] In this embodiment, the situation may refer only to the situation of the target person when the policy is implemented, or may refer only to the situation of the target person when taking the promotion behavior promoted by the policy, or may refer to both of these situations. Furthermore, the situation may include, for example, a situation indicating a location (for example, while working in the office, while working outside the office, on the way to work, while attending class at school, or while traveling).

[0037] As will be described in detail later, the evaluation parameter generation unit 111 calculates the value of each feature included in the behavior promotion level evaluation parameter column 1213 for the state before the policy is implemented for the combination of situation, target, and promotion behavior selected by the policy designer. Hereinafter, the state before the policy is implemented (the state before the policy is implemented) is also referred to as the baseline.

[0038] When a policy based on a policy is implemented on the baseline situation, it is assumed that the value of each feature amount in the baseline changes according to the value of each feature amount of the evaluation parameter corresponding to the policy. The behavior of the change is predetermined for each type of feature amount. Specifically, for example, when a policy based on a policy is implemented, it is assumed that a feature amount X of a predetermined type on an interval scale changes to a value obtained by performing a predetermined calculation on the baseline value and the value indicated in the promotion-to-be-action evaluation parameter field 1213 (for example, the sum, product, difference, or quotient of the baseline value and the value indicated in the promotion-to-be-action evaluation parameter field 1213), and that a feature amount Y of a predetermined type on a nominal scale changes to the value indicated in the promotion-to-be-action evaluation parameter field 1213 (i.e., is overwritten with a value corresponding to the policy).

[0039] Note that there may be feature quantities whose values ​​cannot be defined in each policy and baseline. Feature quantities whose values ​​cannot be defined in each policy and baseline are indicated by "-" in the behavior promotion level evaluation parameter column 1213.

[0040] If there is a feature whose value cannot be defined in at least one of the baseline and the policy direction, the behavior of the change in the feature when the policy according to the policy direction is implemented is also determined in advance, for example, for each type of feature. Specifically, for example, if the value is "-" in at least one of the baseline and the policy direction, there may be a feature of a type whose value is expected to be "-" when the policy according to the policy direction is implemented, or there may be a feature whose value is "-" in only one of the baseline and the policy direction, for which the value of the other is adopted (i.e., if only the value at the baseline is "-", the value of the policy direction is adopted, or if only the value of the policy direction is "-", the value at the baseline is adopted). There may be a feature whose value is "-" regardless of the value at the baseline if the value of the policy direction is "-", or there may be a feature whose value is "-" regardless of the value at the baseline if the value at the baseline is "-".

[0041] The implementability evaluation parameter column 1214 holds, for example, parameters for evaluating the implementability of a policy plan. The implementability evaluation parameters are defined, for example, by one or more implementation conditions (M implementation conditions in this embodiment) for implementing a policy based on the policy plan in the terminal 200. The implementation conditions include, for example, conditions related to resources required of the terminal 200 for implementing the policy based on the policy plan in the terminal 200 (for example, devices or functions possessed by the terminal 200, or the performance of the terminal 200, etc.).

[0042] 2, "Implementation Condition 1" indicates whether the terminal 200 needs to have an input means to implement the policy (or may be whether it is desirable to have an input means), and "Implementation Condition 2" indicates whether the terminal 200 needs to have an information acquisition means for acquiring specific information to implement the policy (or may be whether it is desirable to have an information acquisition means). In addition, there may be other implementation conditions, such as whether there is a means for a target who has performed a promotional behavior to receive a reward.

[0043] For example, in the policy guideline "Commitment," the behavior promotion target person makes a declaration regarding the promotion behavior, so in order to implement "Commitment," the terminal 200 needs to have an input means for accepting the input of the declaration. Also, in the policy guideline "Feedback," for example, the results of the promotion behavior by the behavior promotion target person are communicated to the behavior promoter, so in order to implement "Feedback," the terminal 200 needs to have an information acquisition means for acquiring information indicating the results of the promotion behavior (for example, "amount of power used" when the promotion behavior is "power saving behavior").

[0044] 3 is a diagram showing an example of the data configuration of the policy implementation example table 122. The policy implementation example table 122 includes, for example, an implementation example ID column 1221, a situation column 1222, a target column 1223, a promotion action column 1224, a policy policy column 1225, a content display means column 1226, an implementation condition column 1227, and a content path column 1228.

[0045] The implementation example ID column 1221 holds an implementation example ID that identifies an example (implementation example) of an implemented measure. The situation column 1222 holds information indicating the situation when the measure of the implementation example was implemented. The target person column 1223 holds information indicating the type of target person who uses the terminal 200 in which the measure of the implementation example is implemented.

[0046] The promotion action column 1224 holds information indicating the promotion action promoted in the measure of the implementation example. The measure policy column 1225 holds information indicating the measure policy of the measure of the implementation example. The content display means column 1226 holds information indicating the display means (type of display method) that displayed the content in the measure of the implementation example.

[0047] The implementation condition column 1227 holds information indicating whether the terminal 200 on which the measure of the implementation example was implemented satisfied each of the implementation conditions included in the implementability evaluation parameters. The content path column 1228 holds information indicating the file path where the content of the measure of the implementation example distributed to the target terminal 200 is stored (information indicating the measure content). Note that the measure content of the implementation example may be stored in the auxiliary storage device 102 or in an external database connected to the measure design and distribution system 100.

[0048] 4 is a diagram showing an example of the data configuration of the policy distribution setting table 123. The policy distribution setting table 123 includes a policy distribution ID column 1231, a project ID column 1232, a target person list column 1233, a target person group column 1234, a distribution schedule column 1235, a distribution time column 1236, a distribution method column 1237, a content format column 1238, a content path column 1239, and an access destination column 12310.

[0049] The policy delivery ID column 1231 holds a policy delivery ID that identifies the delivery of policy content for which delivery settings have been completed. The project ID column 1232 holds a project ID that identifies the project to which the policy indicated by the policy content for which delivery settings have been completed belongs. The target person list column 1233 holds information indicating a target person list including target people who use the terminal 200 to which the policy content for which delivery settings have been completed is delivered. The target person group column 1234 holds information indicating a target person group including target people who use the terminal 200 to which the policy content for which delivery settings have been completed is delivered.

[0050] The distribution schedule column 1235 holds information indicating the distribution schedule of the campaign content for which distribution settings have been completed. The distribution schedule may be defined by one or more specified dates, or may be defined by one or more periods. The distribution time column 1236 holds information indicating the distribution time of the campaign content for which distribution settings have been completed. The distribution time may be defined by one or more times, or may be defined by one or more time periods.

[0051] The delivery method column 1237 holds information indicating the delivery method of the policy content for which delivery settings have been completed. The content format column 1238 holds information indicating the format of the policy content for which delivery settings have been completed. The content path column 1239 holds information indicating the file path where the policy content for which delivery settings have been completed is stored (information indicating the policy content). The policy content for which delivery settings have been completed may be stored in the auxiliary storage device 102, or may be stored in an external database connected to the policy design and delivery system 100. The access destination column 12310 holds information indicating the address (e.g., URL (Uniform Resource Locator)) for accessing the policy content when the delivery method is "Web server".

[0052] 5 is a diagram showing an example of the data configuration of the project management table 124. The project management table 124 includes, for example, a project ID column 1241, a project name column 1242, a target person list ID column 1243, a situation column 1244, a target person column 1245, a promotion action column 1246, and a status column 1247.

[0053] The project ID column 1241 holds the project ID. The project name column 1242 holds information indicating the project name. The target person list ID column 1243 holds the ID of the target person list that includes the target persons of the measures belonging to the project. The situation column 1244 holds information indicating the situation of the measures belonging to the project.

[0054] The target person column 1245 holds information indicating the type of target person of the measures belonging to the project. The promotion action column 1246 holds information indicating the promotion action in the measures belonging to the project. The status column 1247 holds information indicating the status of the project. The status of the project indicates, for example, whether the project (or the measures belonging to the project) is not yet implemented, is being implemented, or has been completed.

[0055] 6 is a diagram showing an example of the data configuration of the target person information table 125. The target person information table 125 includes, for example, a target person ID column 1251, a target person column 1252, a target person list ID column 1253, and a target person group column 1254. The target person ID column 1251 holds a target person ID that identifies a target person for action promotion. Note that, for example, the terminal 200 held by the target person is associated with the target person ID, and one target person ID may be associated with one terminal 200, one target person ID may be associated with multiple terminals 200, or multiple target person IDs may be associated with one terminal 200. The target person column 1252 holds information indicating the type of target person indicated by the target person ID.

[0056] The target list ID column 1253 holds a target list ID that identifies the target list in which the target is included. The target group column 1254 holds information indicating the target group in which the target is included. For example, a target list identifies a group of targets of a measure belonging to a project. Also, for example, a target group is a group obtained by further dividing a group included in a target list. For example, by classifying target groups by the user attributes of the targets, whether or not they have taken a certain action, etc., it is possible to select targets to whom a measure will be delivered based on specific user attributes, whether or not they have taken a certain action, etc.

[0057] 7 is a diagram showing an example of the data configuration of the behavior table 126. The behavior table 126 includes, for example, a behavior group ID column 1261 and a promotion behavior column 1262. The behavior group ID column 1261 holds a behavior group ID that identifies the behavior group to which the promotion behavior belongs. The promotion behavior column 1262 indicates a promotion behavior included in the behavior group indicated by the corresponding behavior group ID. Promotion behaviors that belong to the same behavior group ID are considered to be similar behaviors.

[0058] 8 is an explanatory diagram showing an example of an outline of processing by the policy design and distribution system 100. The policy editor UI generation unit 116 selects a policy situation, a policy target, and a promotion action in the policy, for example, according to input from a policy designer.

[0059] The evaluation parameter generation unit 111 generates the values ​​of each baseline behavior promotion evaluation parameter for the situation, the subject, and the promotion behavior (i.e., the value of each parameter before the measure indicating the promotion behavior is implemented by the subject in the situation).

[0060] The action promotion level evaluation unit 112 calculates the action promotion level for each policy based on the baseline action promotion evaluation parameter value and the action evaluation parameter value for each policy shown in the policy table 121. The action promotion level evaluation unit 112 extracts policy measures that have an action promotion effect based on the calculated action promotion level.

[0061] The implementation example acquisition unit 114 acquires implementation examples based on the selected situation and target person from the policy implementation example table 122. The implementability evaluation unit 113 compares the implementation conditions in the acquired implementation examples with the implementation conditions of the implementability evaluation parameters in each policy direction that has a behavior promotion effect, and evaluates the implementability of each policy direction that has a behavior promotion effect.

[0062] The measure editor UI generation unit 116 displays the action promotion level and implementation possibility of each policy measure that has a behavior promotion effect on the policy proposal screen 1000. The measure editor UI generation unit 116 displays a policy editing screen 1100 for accepting editing of the policy content corresponding to the policy measure selected on the policy proposal screen 1000 and distribution settings for the policy content.

[0063] The measure editor UI generation unit 116 stores the distribution settings of the measure content accepted on the measure editing screen 1100 in the measure distribution setting table 123. The measure content distribution unit 115 distributes the measure content edited on the measure editing screen 1100 to the terminal 200 in accordance with the distribution settings.

[0064] Fig. 9 is a flowchart showing an example of the details of the processing by the policy design and distribution system 100. Before the processing in Fig. 9 starts, it is assumed that values ​​in each column of the policy policy table 121, the policy implementation example table 122, the project management table 124, the target person information table 125, and the behavior table 126 are set in advance.

[0065] The policy editor UI generation unit 116 selects a combination of a policy situation, a policy target, and a promotion action in the policy, for example, according to an input from a policy designer (S901). Specifically, for example, the policy editor UI generation unit 116 displays information of each record in the project management table 124 on the display device 105, and allows the policy designer to select any one of the records (i.e., project), thereby selecting a combination of the situation, target, and promotion action corresponding to the record.

[0066] In addition, in step S901, the policy editor UI generation unit 116 can display on the display device 105 the subject IDs and types of subjects included in each subject list indicated by the subject information table 125, as well as the subject IDs and types of subjects included in each subject group indicated by the subject information table 125, allowing the policy designer to select subjects included in a specific subject list or a specific subject group.

[0067] The evaluation parameter generation unit 111 generates a baseline value for each type of feature included in the behavior promotion level evaluation parameter column 1213 of the policy plan table 121 for the combination of the situation, target person, and promotion behavior selected in step S901 (S902). Specifically, for example, the evaluation parameter generation unit 111 generates a baseline value for each feature according to input from a policy designer. The behavior promotion level evaluation unit 112 extracts each record of the policy plan table 121 as a policy plan candidate (S903).

[0068] The behavior promotion level evaluation unit 112 evaluates the behavior promotion level of each of the policy direction candidates (S904). Specifically, for each of the policy direction candidates extracted in step S903, the behavior promotion level evaluation unit 112 calculates the value of each feature amount corresponding to the policy direction candidate in the case where the policy according to the policy direction candidate is implemented for the baseline situation by reflecting the value of each feature amount of the baseline generated in step S902 (as described above, in accordance with the behavior of change predetermined for each type of feature amount).

[0069] Furthermore, for example, a machine learning model is prepared in advance (for example, stored in the auxiliary storage device 102 or memory 103, or an external database connected to the policy design and distribution system 100) that outputs a cooperation rate for promotional behavior (which may indicate the probability that each subject will take promotional behavior, or may indicate the proportion of the number of subjects who take promotional behavior) when each feature included in the evaluation parameters is input.

[0070] The machine learning model is generated by supervised learning using learning data including, for example, values ​​of each feature (parameter for behavioral evaluation) corresponding to the learning policy and correct answer data indicating whether the learning subject took promotion behavior when the policy was implemented.

[0071] For example, the behavior promotion level evaluation unit 112 obtains the cooperation rate when a policy based on the policy candidate is implemented against the baseline situation by inputting the values ​​of each feature into the model for each policy direction candidate when the policy based on the policy candidate is implemented against the baseline situation, and determines the cooperation rate as the behavior promotion level for the policy direction candidate.

[0072] Furthermore, the behavior promotion level evaluation unit 112 acquires the cooperation rate at the baseline by inputting the values ​​of each feature amount of the baseline generated in step S902 into the model. For each policy direction candidate, the behavior promotion level evaluation unit 112 may also calculate the difference between the cooperation rate when the policy according to the policy direction candidate is implemented and the cooperation rate at the baseline, that is, the improvement in the cooperation rate when the policy according to the policy direction is implemented.

[0073] In addition, the behavior promotion level evaluation unit 112 may extract a combination of multiple policy policies (for example, both "commitment" and "feedback" are implemented) as a candidate policy policy by combining not only the policy policies indicated by each record in the policy policy table 121, but also any multiple records included in the policy policy table 121.

[0074] In this case, the action promotion level evaluation unit 112 calculates the action promotion level for each of the policy policy candidates defined by the combination of policy policies, for example, as follows: The action promotion level evaluation unit 112 refers to the value of the feature amount of each type of policy policy included in the combination.

[0075] For example, for a feature of a type whose value corresponding to only one policy policy included in the combination is not "-", the behavior promotion evaluation unit 112 adopts the value corresponding to that one policy policy (i.e., the value other than "-") as the value of the feature of that type in the combination.

[0076] Furthermore, for example, for a feature of a type whose value corresponding to the multiple policy policies included in the combination is not "-", if the values ​​corresponding to the multiple policy policies are all the same value, the behavior promotion evaluation unit 112 adopts that same value as the value of the feature of that type in the combination.

[0077] Furthermore, for example, if the values ​​corresponding to the multiple policy policies included in the combination are different for a type of feature whose value is not "-" and the feature of that type is an ordinal scale feature, the behavior promotion evaluation unit 112 calculates the behavior promotion levels for all patterns when each of the different values ​​is used as the value of the feature of that type in the combination (if different values ​​are used for each of the multiple types of ordinal scale feature, the behavior promotion levels for all patterns when each of the different values ​​is used for each of the multiple types of ordinal scale feature), and uses the highest behavior promotion level as the behavior promotion level for the combination.

[0078] Furthermore, for example, if the values ​​corresponding to the multiple policy policies included in the combination of features of a type that are not "-" include different values, and the feature of that type is a nominal feature, the behavior promotion evaluation unit 112 excludes the combination of policy policies from the candidate policy policies, as it considers the combination to be invalid.

[0079] In general, when multiple policies are combined, they tend to encourage more action than a single policy alone, but tend to be less likely to be implemented than a single policy alone.

[0080] Also, for example, for feature quantities of a type whose values ​​corresponding to all policy guidelines included in the combination are "-", the action promotion level evaluation unit 112 adopts "-" as the value of the feature quantity of that type in the combination.

[0081] For example, a machine learning model may be prepared in advance that, when each feature in the baseline and each feature corresponding to a policy candidate are input, outputs the cooperation rate when the policy according to the policy candidate is implemented. The machine learning model is generated by supervised learning using learning data including, for example, each feature corresponding to the baseline and the policy, and ground truth data indicating the cooperation rate when the policy according to the policy is implemented.

[0082] The action promotion level evaluation unit 112 extracts from the policy plan candidates those policy plans whose action promotion level calculated in step S904 is high based on predetermined conditions (S905). Specifically, for example, the action promotion level evaluation unit 112 may extract policy plans whose action promotion level is greater than a predetermined value (for example, greater than 0, i.e., the implementation of a policy plan is effective), or may extract a predetermined number of policy plans in descending order of action promotion level, or may extract policy plans whose action promotion level is greater than a predetermined value up to a predetermined number.

[0083] The implementation case acquisition unit 114 acquires implementation cases from the policy implementation case table 122 based on the situation and target person selected in step S901, and the implementation feasibility evaluation unit 113 compares the implementation conditions in the acquired implementation cases with the implementation conditions of the implementation feasibility evaluation parameters for each policy policy extracted in step S905, and evaluates the implementation feasibility of each policy policy extracted in step S905 (S906).

[0084] In step S906, the implementation example acquisition unit 114 acquires, for example, from the policy implementation example table 122, a record (implementation example) having the combination of the situation and the target person selected in step S901.

[0085] Also, for example, the implementation example acquisition unit 114 may acquire a record having a combination of the situation, target person, and promotion action selected in step S901 from the policy implementation example table 122. Also, for example, the implementation example acquisition unit 114 may identify a promotion action having the same action group ID as the promotion action selected in step S901 (i.e., a similar action to the promotion action selected in step S901) from the action table 126, and acquire a record having a combination of the situation, target person, and promotion action selected in step S901, and a record having a combination of the situation, target person, and similar action selected in step S901, from the policy implementation example table 122.

[0086] When the implementation case acquisition unit 114 acquires implementation cases using only the situation and the target person without considering the promoting behavior or similar behavior, it can acquire more implementation cases, and when it acquires implementation cases using the promoting behavior and similar behavior, it can acquire implementation cases that are more similar to the measures to be designed.

[0087] In step S906, for each policy direction extracted in step S905, the implementability evaluation unit 113 identifies, among the implementation conditions of the implementability evaluation parameters, implementation conditions for which the value in the implementability evaluation parameter column 1214 is "required." Furthermore, for a policy direction defined by a combination of multiple policy directions, the implementability evaluation unit 113 identifies, among the implementation conditions of the implementability evaluation parameters, implementation conditions for which the value in the implementability evaluation parameter column 1214 is "required" for at least one policy direction included in the multiple policy directions (to calculate the possibility of implementing all of the multiple policy directions).

[0088] For example, for each policy extracted in step S905, the implementability evaluation unit 113 calculates the percentage of implementation cases in which all of the specified implementation conditions are "present" among the number of implementation cases acquired by the implementation case acquisition unit 114 as the implementability of the policy. Also, for example, for each policy extracted in step S905, the implementability evaluation unit 113 may calculate the percentage of implementation cases in which the implementation conditions are "present" among the number of implementation cases acquired by the implementation case acquisition unit 114 for each specified implementation condition, and calculate a predetermined statistic (for example, an average value, etc.) of the percentage for each specified implementation condition as the implementability of the policy.

[0089] The measure editor UI generation unit 116 displays on the display device 105 a measure proposal screen 1000 including a display relating to the behavior promotion level and implementability of the measure outline extracted in step S905 (S907).

[0090] 10 is a diagram showing an example of the screen configuration of a measure proposal screen 1000. The measure proposal screen 1000 includes, for example, a graph display area 1001, a selected information display area 1002, and a measure policy information display area 1003. The graph display area 1001 displays a graph showing the action promotion level calculated in step S904 and the implementation possibility calculated in step S906 for each of the measure policies extracted in step S905 (in the example of FIG. 10, the policy policies having a higher action promotion level than the baseline). The graph also shows the baseline action promotion level.

[0091] In the example of the graph display area 1001 in FIG. 10, the icon with "commitment" and "feedback" written in two lines indicates a policy that is a combination of two policy policies, "commitment" and "feedback."

[0092] By referring to the graph, the policy designer can select a policy that takes into consideration the behavior promotion level and the possibility of implementation. Specifically, from among policies with a high behavior promotion level, it is possible to select a policy that is easier to implement on the terminal 200, and ultimately to provide a policy based on a policy that uses appropriate touch points to the target person for behavior promotion.

[0093] The selected information display area 1002 displays information indicating the situation, target person, and promotion behavior selected in step S901.

[0094] In the graph display area 1001, when one of the policy icons displayed in the graph is selected by input via the input device 104, information about the selected policy is displayed in the policy information display area 1003. In the example of Fig. 10, the "Commitment" icon is selected in the graph display area 1001.

[0095] The policy information display area 1003 displays, for example, the policy selected in the graph display area 1001, an explanatory text corresponding to the policy in the policy table 121, information about the policy (in the example of FIG. 10, information indicating the behavior promotion level of the policy (cooperation rate and improvement level of cooperation rate), implementation conditions required for the policy, and information indicating the implementability of the policy), and information about implementation cases (in the example of FIG. 10, implementation case ID, situation, target person, promotion behavior, and content display means) that match the selected policy among the implementation cases shown in the policy implementation case table 122 (which may be further limited to implementation cases acquired by the implementation case acquisition unit 114 in step S906). In addition, when a selection button in a box indicating each implementation case in the policy information display area 1003 is selected by input via the input device 104, the corresponding implementation case is selected.

[0096] Returning to the explanation of Fig. 9, the policy editor UI generation unit 116 selects a policy policy in the graph display area 1001 in accordance with the input via the input device 104, and displays information about the selected policy policy in the policy policy information display area 1003 (S908). The implementation example acquisition unit 114 acquires an implementation example corresponding to the policy policy selected in step S908 (S909), and the policy editor UI generation unit 116 displays information about the implementation example acquired in step S909 in the policy policy information display area 1003 (S910).

[0097] The measure editor UI generation unit 116 selects an implementation example in the measure policy information display area 1003 in accordance with an input via the input device 104 (S911). The measure editor UI generation unit 116 displays a measure editing screen 1100 on the display device 105 based on the selected implementation example (S912).

[0098] 11 is a diagram showing an example of the screen layout of a measure editing screen 1100. The measure editing screen 1100 includes, for example, a selected information display area 1101, a reference case display area 1102, a content editing area 1103, and a measure distribution setting area 1104.

[0099] The selected information display area 1101 displays information indicating the situation, target person, and promotion action selected in step S901. The reference case display area 1102 displays information regarding the implementation case selected from the policy information display area 1003 in step S911.

[0100] The content editing area 1103 is an area for editing the content to be distributed. When the measure editing screen 1100 is displayed, the measure content acquired from the content path corresponding to the implementation example selected in step S911 is first displayed in the content editing area 1103. The measure editor UI generation unit 116 edits the text (e.g., a message related to the measure) and images in the area surrounded by a dotted line in the content editing area 1103 according to input to the input device 104.

[0101] Note that instead of or in addition to the above-described policy content, for example, policy content (text and images) generated using a generation AI (Artificial Intelligence) may be displayed in the content editing area 1103. When a prompt indicating the policy policy selected in step S908 and the situation and promotion action selected in step S901 (which may be a prompt indicating the policy policy selected in step S908 and the promotion action selected in step S901) is input to the generation AI, policy content (text and images included therein) in line with the policy policy, the situation, and the promotion action is generated.

[0102] The generation AI is stored in advance, for example, in the auxiliary storage device 102 or the memory 103, or in an external database connected to the policy design and distribution system 100. The generation AI is generated by machine learning using previously implemented learning policy content indicating a policy direction, promotion behavior, and situation (if the input information of the generation AI does not require a situation, the learning policy content does not need to indicate the situation) as learning data. Note that if the content editing area 1103 does not display the policy content of the implementation example, and only the policy content generated using the generation AI is displayed, it is not necessary to select an implementation example on the policy proposal screen 1000, and only the policy direction may be selected.

[0103] Furthermore, the policy editor UI generation unit 116 may check whether the policy content edited in the content editing area 1103 by the policy designer conforms to the policy direction selected in step S908.

[0104] Specifically, for example, information indicating syntax and context patterns of text messages related to the policy content for each policy policy is stored in the auxiliary storage device 102 or the memory 103, or in an external database connected to the policy design and distribution system 100. The policy editor UI generation unit 116 performs morphological analysis, syntactic analysis, and / or context analysis processing using a predetermined algorithm on the text messages included in the policy content edited in the content editing area 1103. The policy editor UI generation unit 116, for example, calculates the degree of match between the context pattern obtained by the analysis processing and a pre-stored context pattern corresponding to the policy policy selected in step S908, and may display an alert if the degree of match is low (for example, below a predetermined value). Specifically, for example, the policy editor UI generation unit 116 can calculate, as the degree of match, a similarity between the text messages included in the policy content edited in the content editing area 1103 and the text messages related to the policy content for each policy policy, based on an algorithm such as word2vec.

[0105] Furthermore, for example, information indicating feature patterns of images related to the policy content for each policy direction is stored in the auxiliary storage device 102 or the memory 103, or an external database connected to the policy design and distribution system 100. The policy editor UI generation unit 116 executes image recognition processing using a predetermined algorithm on images included in the policy content edited in the content editing area 1103. The policy editor UI generation unit 116, for example, executes matching between the feature pattern obtained by the image recognition processing and a pre-stored feature pattern corresponding to the policy direction selected in step S908, and may display an alert if the degree of match indicated by the matching is low (for example, equal to or less than a predetermined value).

[0106] The policy distribution setting area 1104 is an area for accepting distribution settings for policy content according to input to the input device 104. Specifically, for example, the policy distribution setting area 1104 accepts settings of information to be stored in a distribution schedule field 1235, a distribution time field 1236, a distribution method field 1237, a content format field 1238, an access destination field 12310, etc. in the policy distribution setting table 123.

[0107] Returning to the description of Fig. 9, the policy editor UI generation unit 116 edits the policy content in the content editing area 1103 in accordance with the input via the input device 104, and sets the distribution of the policy content in the policy distribution setting area 1104 (S913).

[0108] The policy editor UI generation unit 116 determines a content path, saves information indicating the policy content edited in step S913 according to the content path, and saves the distribution settings set in step S913 and information indicating the project ID and target persons of the project selected in step S901 in the policy distribution setting table 123 (S914).The policy content distribution unit 115 distributes the policy content to the terminal 200 according to the distribution settings indicated in the policy distribution setting table 123 (S915).

[0109] In addition, for each project ID, when the distribution schedule for at least one policy content having that project ID begins, the policy content distribution unit 115 changes the status (in the project management table 124) of the project indicated by the project ID corresponding to that policy content in the policy distribution setting table 123 to "In Progress," and when the distribution schedule for all policy contents having that project ID ends, changes the status to "Completed."

[0110] Through the above-described processing, the policy design and distribution system 100 can provide a UI for easily selecting a policy that is highly effective in promoting behavior and that is also likely to clear the constraints of the environment in which the policy is implemented, and can distribute the policy based on that policy. As a result, policy content with a high degree of behavior promotion and in an appropriate format is presented to the behavior promotion target using the terminal 200, increasing the likelihood that the behavior promotion target will take the promotion behavior indicated by the policy content.

[0111] In addition, by displaying the policy proposal screen 1000, the policy design and distribution system 100 can easily allow the policy designer to recognize the degree of behavior promotion and implementation possibility, and can present a large variety of implementation examples corresponding to the policy direction selected by the policy designer.

[0112] Furthermore, the policy design and distribution system 100 allows policy designers to edit policy content from past implementation cases or policy content generated by generation AI on the policy editing screen 1100, so even policy designers who lack the knowledge to generate policy content (for example, knowledge to generate messages and images or knowledge regarding the overall design of policy content) can generate policy content that is highly effective in encouraging behavior.

[0113] 12 is a diagram showing an example of the screen configuration of the policy application effect display screen. After the policy content is distributed, the effect measurement unit 117 measures the effect of the policy content. The effect measurement unit 117 measures the effect for each project ID, for example.

[0114] The effect measurement unit 117 is capable of obtaining information as to whether or not each of the target persons for behavior promotion who use the terminal 200 to which the measure has been distributed has taken the promotion behavior (for example, the target persons for behavior promotion have taken the promotion behavior but the promotion behavior is monitored by the terminal 200 or a specific device, and the monitoring results are sent to the measure design and distribution system 100, or information indicating whether or not the target persons for behavior promotion have taken the promotion behavior is input by the input device 104, etc.).

[0115] Furthermore, the effect measurement unit 117 does not need to be able to identify for each behavior promotion target whether or not the target using the terminal 200 to which the measure was delivered took the promotion behavior, but may be able to obtain information, for example, about the type of target, the target list, or the number of people who took the promotion behavior for each target group.

[0116] The policy application effect display screen 1200 is displayed on the display device 105 by the policy editor UI generation unit 116. The policy application effect display screen 1200 includes, for example, a project information display area 1201, a target person information display area 1202, and an effect graph display area 1203. The project information display area 1201 displays information indicating the project ID, situation, target person, and promotion action for a project selected from the project management table 124, for example, by input by the policy designer via the input device 104.

[0117] The subject information display area 1202 displays a subject list ID corresponding to the project and a pull-down menu for selecting a subject group included in the subject list ID.

[0118] The effect graph display area 1203 displays an effect graph showing a time series of the proportion of the number of subjects who took promotional behavior corresponding to the project to the total number of subjects in the subject group selected in the subject information display area 1202 (i.e., the above-mentioned cooperation rate, which is an example of the behavior promotion degree). The effect graph is generated by the effect measurement unit 117. Note that the effect graph may also show a time series of the absolute number of subjects who took promotional behavior corresponding to the project.

[0119] The effect graph describes a time series, for example, from a predetermined date before the first distribution date of the policy content corresponding to the project (for example, two weeks before the first distribution date) to a predetermined date after the last distribution date of the policy content corresponding to the project (for example, two weeks after the last distribution date) or to the current day. Also, a box indicating a policy distribution ID displayed in the effect graph display area 1203 indicates the distribution schedule of the policy content corresponding to the policy distribution ID.

[0120] The effect graph allows the policy designer to easily recognize the change in the behavior promotion level before and after the distribution of the policy content. In addition, the behavior promotion level calculated in step S904 of the policy policy of the policy content corresponding to the project (i.e., the behavior promotion level predicted before the policy distribution) may also be displayed on the policy application effect display screen 1200.

[0121] Furthermore, implementation examples of the distributed policy content may be stored in the policy implementation example table 122, and at this time, information indicating the effectiveness of the distributed policy content may also be registered. Specifically, for example, the effect measurement unit 117 calculates the average value of the behavior promotion degree from the distribution start date of the policy content to a predetermined number of days after the distribution end date of the policy content as the effectiveness of the distributed policy content. In this case, the policy editor UI generation unit 116 may display information indicating the effectiveness of the implementation example together with the implementation example in the policy policy information display area 1003 of the policy proposal screen 1000.

[0122] Furthermore, for example, when a policy content that encourages a specific promotional behavior is distributed, the effect measurement unit 117 changes the target group in the target information table 125 corresponding to a target who has performed the specific promotional behavior within a predetermined period after the start of distribution of the policy content to, for example, a specific group to which only targets who have performed the promotional behavior can belong, and changes the target group in the target information table 125 corresponding to a target who has not performed the specific promotional behavior within the predetermined period to, for example, a specific group to which only targets who have not performed the promotional behavior can belong. As a result, when different policies are implemented for each group, the policies are automatically switched.

[0123] The present invention is not limited to the above-described embodiments, but includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0124] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software, with a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0125] In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected. [Explanation of symbols]

[0126] 100 Policy design and distribution system, 101 CPU, 102 auxiliary storage device, 103 memory, 104 input device, 105 display device, 106 communication device, 111 evaluation parameter generation unit, 112 behavior promotion degree evaluation unit, 113 implementation possibility evaluation unit, 114 implementation case acquisition unit, 115 policy content distribution unit, 116 policy editor UI generation unit, 117 effect measurement unit, 121 policy policy table, 122 policy implementation case table, 123 policy distribution setting table, 124 project management table, 125 target person information table, 126 behavior table, 200 terminal

Claims

1. An information processing system, a processor and a memory, The memory includes: Policy information indicating a policy for a policy to encourage a target person to take action and implementation conditions required for a terminal owned by the target person to implement the policy in the terminal; Implementation case information indicating implementation cases of the measures distributed in the past, the target users and situations of the measures in the implementation cases, and whether the terminals to which the measures in the implementation cases were distributed satisfied each of the implementation conditions; The degree to which the measures according to the policy guidelines encourage the target person to take action is maintained; The processor: Accepts the designation of the target person and situation, Acquire an implementation example corresponding to the specified target person and situation from the implementation example information; Identifying the policy having a high behavior promotion degree based on a predetermined condition as a policy candidate; Evaluating the possibility of implementing the policy direction candidate based on whether an implementation condition corresponding to the policy direction candidate in the policy direction information is satisfied in the acquired implementation case; An information processing system that generates data for displaying a policy proposal screen including a display showing the policy course candidate, the behavior promotion degree and the implementability of the policy course candidate.

2. 2. The information processing system according to claim 1, The memory stores the behavior promotion levels of measures resulting from combinations of a plurality of the policy directions; The processor: Identifying the single policy or the combination that has a high behavior promotion degree based on the predetermined condition as the policy or combination candidate; An information processing system that evaluates the feasibility of implementing the policy direction candidate for the combination by comparing the implementation conditions required for at least one of the policy direction candidates included in the combination indicated by the policy direction information with the implementation conditions that were met in the acquired implementation case.

3. 2. The information processing system according to claim 1, the policy information indicates a value of a parameter for behavior evaluation of the policy; The memory includes: a baseline value of the behavior evaluation parameter indicating a state in which a measure according to the policy is not being implemented; a learning model that outputs the behavior promotion level when the behavior evaluation parameters are input; the learning model is learned using learning data indicating values ​​of the behavior evaluation parameters corresponding to a learning policy policy and whether a learning subject has taken a behavior when a policy according to the learning policy policy is executed, The processor: calculating a value of the behavior evaluation parameter when a measure according to the policy is implemented based on the value of the behavior evaluation parameter of the baseline and the value of the behavior evaluation parameter of the policy; An information processing system that calculates the behavior promotion level corresponding to the policy based on the calculated value and the learning model.

4. 2. The information processing system according to claim 1, The implementation case information indicates actions promoted in the measures in the implementation case, The processor: Accept the action specification, An information processing system that acquires implementation examples corresponding to the specified target person, situation, and behavior from the implementation example information.

5. 5. The information processing system according to claim 4, the memory holds behavior information indicating groups of behaviors that are similar to each other; The processor: Identifying a similar behavior to the specified behavior from the behavior information; An information processing system that acquires implementation examples corresponding to the specified target person, the specified situation, and the specified behavior or the similar behavior from the implementation example information.

6. 2. The information processing system according to claim 1, The processor: Accepting a selection of the policy direction candidate on the policy proposal screen; An information processing system that generates data for editing the content of measures that promote behavior based on the selected policy direction candidate, and for displaying a policy editing screen for accepting distribution settings for distributing the content to the terminal.

7. 7. The information processing system according to claim 6, The implementation example information indicates the policy of the policy in the implementation example and the content of the policy that has been previously distributed in the implementation example, the policy proposal screen includes a display showing the implementation example corresponding to the policy direction candidate, The processor: Accepting a selection of an implementation example corresponding to the selected policy direction candidate on the policy proposal screen; acquiring content corresponding to the selected implementation example from the implementation example information; An information processing system that accepts editing of the acquired content on the policy editing screen.

8. 7. The information processing system according to claim 6, When the policy and the action are input, the system is connected to a generation AI that outputs content of a policy according to the policy that promotes the action, The processor: Accept the action specification, The selected policy direction candidate and the specified action are input to the generation AI to obtain the content of the policy; An information processing system that accepts editing of the acquired content on the policy editing screen.

9. 7. The information processing system according to claim 6, the memory holds information indicating a context pattern of text messages corresponding to each of the policy directions; The processor outputs an alert based on the degree of match between the context pattern of a text message corresponding to the selected policy direction candidate and the context pattern of a text message included in the content edited on the policy editing screen.

10. 7. The information processing system according to claim 6, The processor: Distributing the content edited on the policy editing screen to the terminal as distribution content based on the distribution settings accepted on the policy editing screen; acquiring a performance record of a behavior indicated by the measure of a target person having a terminal to which the distribution content has been distributed during a first period after the start of distribution of the distribution content; Calculating a behavior promotion level due to the distribution content based on the performance of the behavior; An information processing system that generates data for displaying a policy application effect display screen including a display showing the calculated behavior promotion degree and the behavior promotion degree corresponding to the selected policy course candidate.

11. 11. The information processing system according to claim 10, The implementation example information indicates the policy of the policy in the implementation example and the content of the policy that has been previously distributed in the implementation example, the policy proposal screen includes a display showing the implementation example corresponding to the policy direction candidate, The processor: storing information indicating an implementation example of the distribution content, the specified target person and situation, and whether the terminal to which the distribution content was distributed satisfied each of the implementation conditions in the implementation example information; Accepting a selection of an implementation example corresponding to the selected policy direction candidate on the policy proposal screen; acquiring content corresponding to the selected implementation example from the implementation example information; An information processing system that includes, on the policy editing screen, a display showing the acquired implementation examples and the calculated behavior promotion level corresponding to the implementation examples.

12. 11. The information processing system according to claim 10, The processor: calculating a ratio of subjects who have a terminal to which the distribution content has been distributed and who have taken the behavior indicated by the measure during a second period including the distribution period indicated by the distribution setting of the distribution content, based on the results of the behavior; An information processing system that includes a graph showing the second period and the ratio on the policy application effect display screen.

13. 11. The information processing system according to claim 10, The memory holds subject information indicating the subject and a subject group to which the subject belongs; The processor: During the first period, a target group corresponding to a target person who has a terminal to which the distribution content was distributed and who has taken the behavior indicated by the policy is changed in the target person information to a first target group to which the target person who took the behavior belongs; An information processing system that changes the target group corresponding to a target person in the target information who has a terminal to which the distribution content was delivered and who has not taken the behavior indicated by the measure during the second period to a second target group to which targets who have not taken the behavior belong.

14. An information processing method by an information processing system, the information processing system includes a processor and a memory; The memory includes: Policy information indicating a policy for a policy to encourage a target person to take action and implementation conditions required for a terminal owned by the target person to implement the policy in the terminal; Implementation case information indicating implementation cases of the measures distributed in the past, the target users and situations of the measures in the implementation cases, and whether the terminals to which the measures in the implementation cases were distributed satisfied each of the implementation conditions; The degree to which the measures according to the policy guidelines encourage the target person to take action is maintained; The information processing method includes: The processor accepts a designation of a target person and a situation; The processor acquires an implementation example corresponding to the specified target person and situation from the implementation example information, The processor identifies the policy or policy having a high behavior promotion degree based on a predetermined condition as a policy or policy candidate; The processor evaluates the implementability of the policy direction candidate based on whether an implementation condition corresponding to the policy direction candidate in the policy direction information is satisfied in the acquired implementation example; An information processing method in which the processor generates data for displaying a policy proposal screen including a display showing the policy course candidate, the behavior promotion degree and the implementability of the policy course candidate.

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