Apparatus and method for analyzing social participation behavior

Abstract

To provide a device and a method for analyzing a social participation action which realize provision of an incentive to various different types of persons concerned regarding a social participation action of a participant.SOLUTION: In an action analysis support system, an action analyzer 10 of an analysis service sensor 1 analyzes a social participant action of a participant, and includes: an input unit 11 for receiving positional information showing a movement history of each of plural participants; an index calculation unit 14 for calculating a social participation index as social participation information showing a social participation action of each participant specified by the positional information; and an incentive value calculation unit 15 for calculating an incentive value showing an incentive to a person concerned regarding the social participation action including a social participation action provider who provides a place for a social participation action according to a social participation index.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a technique for analyzing the behavior of participants, particularly social participation behavior. In particular, the present invention relates to a technique for providing incentives to activate social participation behavior. Note that the term "participant" includes various concepts related to people, such as residents, customers, users, and related parties. [Background technology]

[0002] As we enter an aging society, health problems among the elderly, such as dementia and nursing care issues, are becoming evident. It is becoming clear that by stimulating the social participation behavior (including social participation activities) of the elderly, it is possible to prevent the onset of dementia and transition to nursing care. In other words, in addition to the conventional diet and exercise, it is important to support and stimulate social participation behavior as a health indicator.

[0003] Here, in order to activate some kind of behavior, it is conceivable to give incentives such as points according to the behavior. It is conceivable to give such incentives to various related parties and organizations (hereinafter simply referred to as related parties) related to the behavior. For example, Patent Document 1 discloses that points are given to multiple related parties for the behavior of searching on the Internet. Specifically, it discloses that member points are given to members who perform searches according to the number of searches, advertising fees, etc., and group points are given to searched groups (see steps 0042 to 0046). In addition, a service that gives points to purchasers of products according to the purchase amount is also commonly used. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2010-157056 A Summary of the Invention [Problem to be solved by the invention]

[0005] Here, in the conventional technology such as Patent Document 1, there are resources for granting points, such as advertising revenue and sales revenue. Therefore, calculation of points can be realized in a simple framework of returning these resources. In contrast, social participation behavior is not an activity that directly involves sales, etc. For this reason, the technology of Patent Document 1, etc. cannot be applied as is to grant incentives such as points for social participation behavior.

[0006] In addition, in order to promote social participation behavior, not only the efforts of each individual is important, but also the cooperation of social participation providing organizations and their managers, which are places where people can interact with each other. In this way, social participation behavior involves stakeholders and organizations (hereinafter simply referred to as stakeholders) such as participants, social participation providing organizations, and social participation behavior providers such as their managers. More specifically, there are various types of social participation behavior providers, such as non-profit organizations for hobbies and volunteers, and for-profit organizations such as retail stores and sports facilities. In other words, stakeholders are not limited to product sellers, as in Patent Document 1 and the like. Patent Document 1 also did not consider providing incentives to stakeholders for such various types.

[0007] Therefore, an object of the present invention is to provide incentives to various related parties regarding the social participation behavior of participants. [Means for solving the problem]

[0008] In order to solve the above problems, the present invention calculates an incentive value that indicates an incentive for related parties and organizations (institutions) regarding social participation behavior. Note that incentives include points for participants and benefits for providers who provide a place for social participation behavior.

[0009] More specifically, in a social participation behavior analysis device that analyzes the social participation behavior of participants, an input unit that receives location information indicating a movement history of each of a plurality of participants; a discrimination unit that uses the location information to create behavior history information indicating behavior histories of the plurality of participants, and discriminates social participation categories of the plurality of participants based on the location information; The above Social Participation CategoryThe above-mentioned Multiple Social participation information showing the social participation behavior of each participant an index calculation unit for calculating a social participation index that indicates the state of involvement with society included in the , the above Social participation index In response to the above, the venue for social participation actions will be The place of the social participation behavior indicated by the facility included in the behavior history information Social participation action provider and said plurality of participants The social participation behavior analysis device includes an incentive value calculation unit that calculates an incentive value indicating an incentive for a person involved in the social participation behavior.

[0010] Furthermore, the present invention also includes a social participation action support method using the above-mentioned social participation action support device, a computer program for causing a computer to execute this method, and a storage medium storing this program. Effect of the Invention

[0011] According to the present invention, it is possible to provide incentives that correspond to the actual state of social participation behavior. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram showing the concept of an embodiment of the present invention. [Diagram 2] FIG. 1 is a system configuration diagram of a behavior analysis support system according to an embodiment of the present invention. [Diagram 3] FIG. 1 is a configuration diagram of a behavior analysis device according to an embodiment of the present invention. [Figure 4] FIG. 2 is a sequence diagram showing an overall process according to an embodiment of the present invention. [Diagram 5] FIG. 4 is a diagram showing an example of participant information used in an embodiment of the present invention. [Figure 6] FIG. 4 is a diagram showing an example of position information used in an embodiment of the present invention. [Figure 7] 11 is a flowchart showing a social participation category determination process in an embodiment of the present invention. [Figure 8] FIG. 2 is a diagram showing the concept of behavior history information used in an embodiment of the present invention. [Figure 9A] FIG. 2 is a diagram showing an example of a POI table used in an embodiment of the present invention. [Figure 9B] FIG. 4 is a diagram showing behavior history information used in one embodiment of the present invention. [Figure 10] FIG. 13 is a diagram showing an example of a social participation classification table used in an embodiment of the present invention. [Figure 11] FIG. 13 is a diagram showing an example of a flowchart illustrating details of a social participation category determination process in an embodiment of the present invention. [Figure 12] FIG. 13 is a flowchart showing details of a social participation index calculation process according to an embodiment of the present invention. [Figure 13] FIG. 13 is a diagram showing an example of a social participation weight table used in an embodiment of the present invention. [Figure 14] FIG. 11 is a graph showing an example of relationship information of stay time according to an embodiment of the present invention. [Figure 15] FIG. 13 is a graph showing an example of relationship information regarding the number of combinations of transportation modes according to an embodiment of the present invention. [Figure 16] FIG. 13 is a graph showing an example of related information regarding the number of visited facilities according to an embodiment of the present invention. [Figure 17] FIG. 13 is a graph showing an example of related information on the number of visitors according to an embodiment of the present invention. [Figure 18] FIG. 13 is a diagram showing a display example (part 1) of a social participation index or number of social participations in an embodiment of the present invention. [Figure 19] FIG. 13 is a diagram showing a display example (part 2) of a social participation index or number of social participations in an embodiment of the present invention. [Figure 20] 1 is a flowchart showing a data analysis (1) process in an embodiment of the present invention. [Figure 21] FIG. 1 shows the display contents of data analysis (1) in one embodiment of the present invention. [Figure 22] 11 is a flowchart showing a process of data analysis (2) in an embodiment of the present invention. [Figure 23] FIG. 2 is a diagram showing individual tally information created in an embodiment of the present invention in the form of an individual tally information table (UT). [Figure 24] 11 is a flowchart showing a process of data analysis (3) in an embodiment of the present invention. [Diagram 25]FIG. 2 is a diagram showing facility-specific tally information created in an embodiment of the present invention in the form of a facility-specific tally information table (PT). [Figure 26] 11 is a flowchart showing a process for calculating a benefit amount in an embodiment of the present invention. [Figure 27] FIG. 13 is a diagram showing a benefit management table used in one embodiment of the present invention. [Figure 28] FIG. 13 is a diagram showing a benefit summary table (BT) used in one embodiment of the present invention. [Figure 29] 11 is a flowchart showing a point calculation process according to an embodiment of the present invention. [Diagram 30] FIG. 13 is a diagram showing a point management table used in one embodiment of the present invention. [Diagram 31] FIG. 2 is a diagram showing a points tally table (AT) used in one embodiment of the present invention. [Diagram 32] FIG. 4 is a diagram showing a display screen of an operator terminal in an embodiment of the present invention. [Diagram 33] FIG. 2 is a diagram showing a display screen of a mobile terminal according to an embodiment of the present invention. [Diagram 34] FIG. 13 is a diagram showing a total visitor count calculation table used in one embodiment of the present invention. [Diagram 35] FIG. 13 is a diagram showing a visitor number calculation table used in one embodiment of the present invention. [Diagram 36] FIG. 11 is a diagram showing facility-specific additional information used in one embodiment of the present invention. [Figure 37] 11 is a flowchart showing a process for determining a point unit price in an embodiment of the present invention. [Figure 38] FIG. 2 is a diagram for explaining a method for estimating the total number of points (P-all) for a year in one embodiment of the present invention. [Figure 39] FIG. 13 is a diagram showing a usage frequency management table in an embodiment of the present invention. [Diagram 40] FIG. 11 is a diagram showing a facility category table used in one embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] An embodiment of the present invention will be described below with reference to the drawings. First, the concept of this embodiment will be described with reference to FIG. 1. In regions A and B, participants such as residents carry mobile terminals 20-1, 20-2, and 20-3 to perform social participation actions. For this reason, each mobile terminal 20-1, 20-2, and 20-3 uses a GPS function or the like to obtain location information associated with the participants' social participation actions. Note that a region is a concept that includes so-called districts, and its units can be arbitrarily set to prefectures, cities, towns, villages, school districts, villages, and the like. Also, a region is an example of a unit society in this embodiment. The unit society includes organizations such as companies and health insurance associations, and local communities.

[0014] Here, this social participation behavior includes travel to and activities at facilities such as one's home, factory (place of work), store, fitness club, gymnasium, community center, and office (place of work). Stores also include grocery stores, convenience stores, pharmacies, liquor stores, and supermarkets. These facilities are provided as "places" for social participation behavior by social participation behavior providers such as facility owners, operators, and users. Participants are not limited to activities within their local area, but also engage in social participation behavior across different regions.

[0015] Then, the behavior analysis device 10 installed in the analysis service center 1 collects location information from each of the mobile terminals 20-1, 20-2, and 20-3. The behavior analysis device 10 uses this and data from the database 17 to identify the social participation behavior of the participants, and executes information processing to grant incentives to the social participation behavior providers and participants based on this. This information processing includes calculation of an incentive value that identifies the incentive. The location information of the participants can also be obtained from facilities such as fitness clubs. The behavior analysis device 10 can also be called a social participation behavior information analysis device. The incentive includes monetary value such as points and benefits. The form of the incentive also includes valuable information, virtual currency, and the like.

[0016] The processing results of the behavior analysis device 10 are output to the operation management terminals 18-1, 18-2, the mobile terminals 20-1, 20-2, 20-3, and the data utilization system. Here, the processing results include social participation information identified based on the location information of the participants and incentive values ​​calculated based on the information. Note that in this embodiment, the social participation index, which is included in the social participation information and indicates the participant's state of involvement with society, is used as an example for explanation.

[0017] The data utilization system outputs the analysis results according to the analysis instructions. The data utilization system is expected to be used by government agencies, insurance companies, nursing care facilities, fitness clubs and other facility management companies, and point management companies in regions A and B. Furthermore, the analysis results include environmental indicators that indicate the ease of participation for each unit of society such as a region, various aggregated information, policy plans using these, and information to support these plans.

[0018] Next, a system configuration diagram of a behavior analysis system for realizing the concept shown in FIG. 1 is shown in FIG. 2. This behavior analysis support system includes a behavior analysis device 10 and various devices operating in each facility 2-1, 2-2, 2-3. This behavior analysis support system also includes a data utilization system connected via a network 80 such as the Internet. The data utilization system includes computer systems of various institutions such as a fitness club system 30, an insurance company system 40, a nursing care facility management company system 50, a point management company system 60, and local administrative agency systems 70-1, 70-2. Here, each data utilization system has a server and a terminal. Among these, the terminal of the data utilization system operated by the social participation behavior provider is called a provider management terminal.

[0019] In this embodiment, the incentive value is calculated by the behavior analysis device 10, but the incentive value may be calculated by the point management company system 60, the insurance company system 40, or the administrative agency systems 70-1 and 70-2. Furthermore, the incentive value may be calculated by the point management company system 60, and the insurance company system 40 or the administrative agency systems 70-1 and 70-2, calculating the amount of payment to the social participation behavior provider.

[0020] Each device constituting the behavior analysis system will be described below. Behavior analysis device 10 is realized by a computer device such as a server provided in analysis service center 1. Behavior analysis device 10 has input unit 11, output unit 12, discrimination unit 13, index calculation unit 14, incentive value calculation unit 15, data analysis unit 16, and database 17.

[0021] The input unit 11 and the output unit 12 have an interface function for connecting to a network 80 and each of the operation management terminals 18-1 and 18-2.

[0022] The discrimination unit 13 discriminates the social participation category of the participant based on the location information. The index calculation unit 14 calculates the social participation index of the participant based on the social participation category. The incentive value calculation unit 15 calculates an incentive value indicating an incentive for related parties including the participant and the social participation behavior provider. Here, the incentive value calculation unit 15 may be realized as a point calculation unit that calculates the number of points, which is a type of incentive, or a benefit amount calculation unit that calculates the benefit amount. Furthermore, the data analysis unit 16 performs various data analyses using the social participation index and the like. Here, the discrimination unit 13 and the index calculation unit 14 calculate the social participation index, which is a type of social participation information. Therefore, these can also be realized as a social participation information identification unit that identifies the social participation information. The details of each of these units will be described later, but they can be realized by a computer program (software) or dedicated hardware or FPGA (Field-Programmable Gate Array). Furthermore, the database 17 stores various data used in the behavior analysis device 10.

[0023] Furthermore, analysis service center 1 is provided with operation management terminals 18-1, 18-2 connected to behavior analysis apparatus 10. Each of operation management terminals 18-1, 18-2 outputs instructions regarding information processing to behavior analysis apparatus 10 and displays the processing results of behavior analysis apparatus 10.

[0024] Next, various devices operating in each of the facilities 2-1, 2-2, and 2-3 will be described. First, in the fitness club 2-1, a mobile terminal 20-1 carried by the participant, a detection device 21 for detecting the participant, and a counter terminal 22 operate. Each of these devices acquires the location information of the participant, and outputs the acquired location information to the behavior analysis device 10 via the network 80. Here, the mobile terminal 20-1 can be realized by a smartphone or a wearable GPS sensor, and can acquire location information using a GPS function. The detection device 21 can be realized by a camera, and identifies the participant by image recognition technology, and the counter terminal 22 identifies the participant by using membership information and acquires location information of the fitness club 2-1. Here, a fitness club is given as an example of a facility in FIG. 2, but the same applies to gymnasiums and stores as shown in FIG. 1.

[0025] Detection device 21 and counter terminal 22 are connected to fitness club system 30 via intranet 90. Mobile terminal 20-1 holds participant identification information, and is connected to behavior analysis device 10 via network 80 such as intranet 90 or the Internet.

[0026] Next, the data utilization system will be described. These are realized by computer systems used by various institutions that use the data. First, the fitness club system 30 can be used at the fitness club headquarters, and can be connected to the detection device 21 and counter terminal 22 installed in the fitness club 2-1 via the intranet 90. The fitness club system 30 uses the analysis results of the behavior analysis device 10 to support the formulation of various measures. The measures include the creation of menus for fitness club members, the use of points given by the point management company, store opening plans, etc.

[0027] The insurance company system 40 is used by an insurance company that sells life insurance and the like. The insurance company system 40 uses the analysis results of the behavior analysis device 10 to support the formulation and management of various policies. The policies include the development of insurance products. The nursing care facility management company system 50 is used by a nursing care facility management company that manages nursing care facilities. The nursing care facility management company system 50 uses the analysis results of the behavior analysis device 10 to support the formulation and management of various policies. The policies include the construction of facilities, the formulation of expansion plans, and the formulation and development of management policies. The point management company system 60 is used by a point management company that manages and manages a point system that can be acquired and used in multiple services. The point management company system 60 uses the information processing results of the behavior analysis device 10 to grant points to participants according to the number of points included in the incentive value calculated by the behavior analysis device 10.

[0028] Furthermore, the administrative agency systems 70-1 and 70-2 are used in city halls, prefectural offices, and the like. The administrative agency systems 70-1 and 70-2 use the analysis results of the behavior analysis device 10 to support the formulation and operation of various policies. The policies in the administrative agency systems 70-1 and 70-2 include various policies for nursing care, public insurance, and the like. For example, the policy for nursing care involves grasping the balance of supply and demand for services, such as grasping the relationship between the elderly population and the supply of nursing care services in a region (at the municipal level, or at the school district level, such as at the elementary and junior high school level), and implementing policies such as supporting the entry of nursing care service providers into regions where high demand is expected. For example, the policy for public insurance involves determining insurance rates that take into account the future population of the region, insurance premium payments, health care projects, and nursing care prevention projects, and formulating policies to popularize health care projects and nursing care prevention projects.

[0029] Here, the configuration of the data utilization system will be briefly explained using administrative agency systems 70-1 and 70-2. Administrative agency systems 70-1 and 70-2 execute main processing using administrative agency servers 71-1 and 71-2, respectively. Administrative agency servers 71-1 and 71-2 are connected to administrative agency terminals 72-1 and 72-2, and receive instructions regarding processing and output processing results. Note that multiple administrative agency terminals 72-1 and 72-2 may be provided. Note that various organizations that use data may include health-related organizations such as hospitals and health insurance associations.

[0030] This concludes the explanation of the overall behavior analysis support system, and we will now explain the details of behavior analysis apparatus 10, which executes the main processing of this embodiment. Figure 3 is a configuration diagram of behavior analysis apparatus 10. In this embodiment, behavior analysis apparatus 10 is realized by a server that executes processing according to a program. For this reason, behavior analysis apparatus 10 has a processing device 101, an I / F device 102, a main memory device 103, and a memory device 104, which are connected to each other via a communication path.

[0031] Here, the processing device 101 can be realized by a processor such as a CPU, and executes calculations according to various programs described later. The I / F device 102 has an interface function for connecting to the network 80 and the operation management terminals 18-1 and 18-2, and corresponds to the input unit 11 and the output unit 12 in FIG.

[0032] The main memory device 103 can be realized by a so-called memory, and programs are deployed for the calculations in the processing device 101. The memory device 104 can be realized by a storage such as a hard disk drive, and stores programs and various information. Here, the programs include a discrimination program 130, an index calculation program 140, an incentive value calculation program 150, and a data analysis program 160.

[0033] These programs correspond to the respective units in FIG. 2 as follows. Discrimination program 130: Discrimination unit 13 Index calculation program 140: Index calculation unit 14 Incentive value calculation program 150: Incentive value calculation unit 15 Data Analysis Program 160: Data Analysis Section 16 Furthermore, each program is distributed via network 80 or stored in a storage medium and installed in behavior analysis device 10. Furthermore, each program is not an independent program, but each program can be realized by a constituent module.

[0034] The storage device 104 also stores the following information: participant information 171, location information 172, a POI table 173, a facility category table 174, behavior history information 175, a social participation classification table 176, a social participation weight table 177, social participation analysis data 178, a benefit management table 179, a benefit tally table 180, a points management table 181, a points tally table 182, a total visitor count calculation table 183, a visitor count calculation table 184, facility-specific additional information 185, a usage frequency management table 186, a facility-specific tally information table 187, and a person-specific tally information table 188. These can be treated as the database 17 shown in FIG. 2.

[0035] Furthermore, in this embodiment, points and benefits are used as incentives. However, the incentive may be at least one of points and benefits, or may be other valuable information, virtual currency, etc. Therefore, the tables for calculating the incentive value are not limited to the benefit management table 179, the benefit tally table 180, the point management table 181, and the point tally table 182. Furthermore, these various information and tables will be explained together with the processing flow explained below.

[0036] Next, the processing flow of this embodiment will be described. At this time, first, the calculation of the social participation index, which is an example of the social participation information, will be described, and then the calculation of the incentive value will be described. In the description of the processing flow, the respective units shown in FIG. 2 will be mainly described. FIG. 4 is a sequence diagram showing the entire processing in this embodiment. This processing is for identifying the social participation behavior of participants such as residents, and the behavior analysis device 10 stores participant information 171 related to the participants. An example of the participant information 171 is shown in FIG. 5. The participant information 171 includes UID, registration date, gender, date of birth, home longitude, home latitude, home altitude, home facility name, workplace longitude, workplace latitude, workplace altitude, workplace altitude, and workplace facility name. The UID is information for identifying the participant, and may also include the name. The registration date indicates the date and time when the participant information in question was registered. However, this information may be up to the date and time. The gender is set to 1 for male and 2 for female.

[0037] The date of birth is the date of birth of the participant. The home latitude, workplace latitude, and home altitude are location information of the participant's home, and may be substituted with the address. The home facility name may be the name of the apartment or building where the participant lives. In this embodiment, various facilities and their operators are used as examples of social participation behavior providers.

[0038] The workplace longitude, workplace latitude, and workplace altitude are location information of the workplace of the participant, and may be substituted with the address. The workplace facility name may be the name of the workplace building, factory name, or company name. As described above, participant information 171 indicates the attributes of the participant, particularly information related to location. Each step will be explained below.

[0039] First, in step S1, each of mobile terminals 20-1, 20-2, and 20-3 (hereinafter simply referred to as mobile terminal 20) acquires location information associated with the movement of the participants. An example of location information 172 is shown in FIG. 6. As shown in FIG. 6, location information 172 is information indicating the movement history of the participants. FIG. 6 shows multiple pieces of location information 172 accumulated in behavior analysis device 10. Therefore, each record in FIG. 6 represents one piece of location information 172 detected by mobile terminal 20.

[0040] Here, the location information 172 includes UID, No, positioning time, latitude, longitude, positioning accuracy, altitude, moving speed, moving direction, and number of steps. No is information for identifying each participant, that is, the location information for each UID. The positioning time indicates the time when the mobile terminal 20 acquires the location information, for example, when it measures the position. The positioning time may be the time indicated by the OS of the mobile terminal 20 or the time obtained as a result of positioning, such as GPS time. The latitude and longitude indicate the location information acquired by the mobile terminal 20. The positioning accuracy is the accuracy in the horizontal direction.

[0041] The altitude, direction of movement, speed of movement, and acceleration of movement can be obtained as positioning results by GPS. The direction of movement can be described, for example, with north being zero degrees. The number of steps can be obtained using the positioning results by an acceleration sensor or GPS, and indicates the number of steps taken by the participant.

[0042] The location information 172 can be acquired by using a GPS function or a location detection function such as a gyro of the mobile terminal 20. Here, the mobile terminal 20 can be realized by a smartphone or the like as described above. This step may also be executed by a detection device 21 or a counter terminal 22 installed in a facility that is the destination of the participant. These pieces of location information are the installation positions, and the participant's location information can be specified by detecting and identifying the participant who has visited the facility.

[0043] Next, in step S2, mobile terminal 20 outputs the acquired location information to behavior analysis device 10. For this purpose, mobile terminal 20 transmits location information at a predetermined cycle via network 80. Furthermore, when location information 172 is acquired by detection device 21 or counter terminal 22, the location information is transmitted further via intranet 90 using communication devices installed in fitness club system 30 or fitness club 2-1.

[0044] Next, in step S3, input unit 11 of behavior analysis device 10 accepts location information 172 from mobile terminal 20. Then, in step S4, discrimination unit 13 discriminates a social participation category in the participant's behavior based on location information 172. As the name suggests, this social participation category is information that indicates a classification of the participant's social participation behavior. Here, the details of the social participation category discrimination process will be described with reference to the flowchart shown in FIG.

[0045] First, in step S41, the discrimination unit 13 creates the behavior history information 175 from the position information 172 and the POI table 173. The concept of this behavior history information 175 will be described with reference to FIG. 8. FIG. 8 shows a situation in which an arbitrary participant leaves home P0, stops at various places (P1 to P6), and returns to home P0. First, the participant moves from home P0 to place P1 as behavior B(0). Next, the participant performs behavior B(1) at place P1. After behavior B(1), the participant moves to the next destination, place P2, by performing behavior B(2). In this way, behavior history information 175 indicating the behavior history of the participant is specified by a set (e.g., repetition) of movements at a goal value and actions at a goal.

[0046] Based on this concept, the discrimination unit 13 creates the behavior history information 175. For this reason, when creating the behavior history information 175, the discrimination unit 13 first extracts the location information of the destination from the received location information 172. For this reason, the discrimination unit 13 sets, as the destination location information, the location information 172 that has a predetermined number (predetermined time) of location information within a predetermined range of latitude and longitude. Note that, at this time, it is desirable for the discrimination unit 13 to extract the first or last location information included in the predetermined number of location information as a representative. Then, the discrimination unit 13 creates the behavior history information 175 from the extracted location information and the POI table 173.

[0047] Here, first, an example of the POI table 173 is shown in FIG. 9A. The POI table 173 is a table showing points of interest, and places (latitude, longitude, etc.) are associated with information about facilities. For example, the POI table 173 may be realized by a map database. The POI table 173 includes a PID, a registration time, a latitude, a longitude, an altitude, a facility size, a facility name, an address, a parent facility PID, and a facility category. Here, the PID is information for identifying a destination. The registration time records the timing at which the facility was registered. The latitude, longitude, and altitude indicate the location of the facility. The facility name and address indicate the name and address of the facility, respectively. In addition, the parent facility PID is the PID of the facility in which the facility is located. For example, in the example of FIG. 9A, if "XX Pharmacy" with PID=2 and "XX Restaurant" with PID=3 are operated in "XX Shopping Center" with PID=7, which is a parent facility, their parent facility PID is "7". For facilities that do not have a parent facility, a null "-" is recorded in the parent facility PID. The facility category indicates the category of the facility.

[0048] Furthermore, the facility category table 174 is a table in which facility names and facility PIDs are associated with facility categories indicating their classification. FIG. 40 is a diagram showing the facility category table 174 used in this embodiment. As shown in FIG. 40, the facility category table 174 is a table for each facility similar to the POI table 173. However, among the items of the POI table 173, it has the items of PID, facility name, and facility category. Therefore, the POI table 173 and the facility category table 174 may be configured as one table. In this case, the facility category table 174 may be omitted, and only the POI table 173 may be provided.

[0049] For this reason, the discrimination unit 13 searches the POI table 173 using the latitude and longitude of the extracted location information as keys, and identifies the facility size, facility name, address, parent facility PID, and facility category. The facility category can also be identified from the facility name and facility PID. As a result, the action history information 175 in FIG. 9B is created. The discrimination unit 13 can also identify the facility names "home" and "workplace" using the participant information 171. However, the facility names "home" and "workplace" may be identified according to input at the operation management terminals 18-1 and 18-2, or resident registration information in the administrative agency systems 70-1 and 70-2 may be used.

[0050] Here, the behavior history information 175 is shown in FIG. 9B. The behavior history information 175 is created by the discrimination unit 13 from the received location information 172 and POI table 173, and includes UID, BID, movement start time, movement start facility PID, movement end time, movement end facility PID, behavior type, movement distance, number of steps, and calories burned. Among these, the BID is information for identifying the behavior of the behavior history information 175, and is given by the discrimination unit 13. The movement start time and the movement end time are the time of departure from the destination and the time of arrival in the corresponding behavior. The movement start facility PID and the movement end facility PID are information for identifying the facility that is the departure point and the facility that is the destination in the corresponding behavior. The behavior type can be identified by the movement speed of the location information 172, with 0 indicating stay and 1 indicating movement. Similarly, the movement means can be identified from the movement speed. For example, it can be identified by associating each movement speed with a movement means.

[0051] The moving distance, the number of steps, and the calories burned indicate the moving distance, the number of steps, and the calories burned when the corresponding action is moving. These may be specified based on the body shape of the participant, which is recorded in the participant information 171. This concludes the explanation of the action history information 175 created in step S41, and we will now proceed to the explanation of step S42.

[0052] In step S42, the discrimination unit 13 performs behavior discrimination using the behavior history information 175. That is, it discriminates each destination. Specifically, from the behavior history information 175, a movement end facility PID in a record of behavior type=0, that is, a stay, is extracted as a destination. Then, the discrimination unit 13 collates the movement end facility PID with the POI table 173 to identify a facility category.

[0053] Next, in step S43, the discrimination unit 13 judges whether the identified facility category can be matched with the social participation classification table 176. As a result, if the match is possible (possible), the process proceeds to step S45. Then, in step S45, the discrimination unit 13 checks the social participation classification table 176 to identify the social participation category corresponding to the identified facility category. The social participation classification table 176 is shown in FIG. 10. The social participation classification table 176 shows the correspondence between the social participation category and the facility category. Here, the facility category can be set based on the classification item name of the Japan Standard Industrial Classification (revised in October 2013) (implemented on April 1, 2014) or with reference thereto. In addition, if multiple social participation categories are implemented in one facility, these may be additionally input. In addition, a dialog may be displayed on the user screen of the operation management terminal 18-1, 18-2 or the mobile terminal 20, and input of the social participation category may be accepted in response to the dialog. Alternatively, the social participation category may be estimated and automatically input from calendar information of the user of the mobile terminal 20 or the like.

[0054] Furthermore, in step S43, if matching cannot be performed in the social participation classification table 176 (impossible), the process proceeds to step S44.

[0055] Then, in step S44, the discrimination unit 13 executes a social participation category discrimination process. The details of this social participation category discrimination process will be described with reference to FIG.

[0056] First, in step S450, the discrimination unit 13 initializes the BID of the target action history information, that is, sets it to 0. Then, in step S451, the discrimination unit 13 identifies the facility category of the action history information. This may be the one identified in step S42.

[0057] Next, in step S452, the discrimination unit 13 acquires schedule data of the participant. This schedule data can be acquired from the mobile terminal 20 or the like. Next, in step S453, the discrimination unit 13 judges whether the schedule in the acquired schedule data is a sports-related hobby. To this end, the discrimination unit 13 uses the schedule information to identify a schedule that corresponds to the target's action history information. Then, the discrimination unit 13 judges whether the content described as the schedule is a sports-related hobby by using language processing or the like.

[0058] As a result, if the hobby is related to sports (Y), the process proceeds to step S457. If the hobby is not related to sports (N), the process proceeds to step S454.

[0059] Next, in step S454, the discrimination unit 13 acquires acceleration information of the participant from the action history information or the position information 172. Then, in step S455, the discrimination unit 13 judges whether the amount of physical activity is high based on whether the acquired acceleration information is equal to or greater than a predetermined value. In other words, if it is equal to the predetermined value, it is judged that the amount of physical activity is high. As a result, if it is high (Y), the process proceeds to step S457, and if it is not high (N), the process proceeds to step S456.

[0060] Next, in step S456, the discrimination unit 13 identifies the corresponding behavior as a cultural hobby (Hobbies (Cultural)). In addition, in step S457, the discrimination unit 13 identifies the corresponding behavior as a sports hobby (Hobbies (Sports).

[0061] Next, in step S458, the discrimination unit 13 judges whether there is any other data to be processed, that is, any record. As a result, if there is no other data (N), the process is terminated. Also, if there is other data (Y), the process proceeds to step S459. Then, in step S459, the discrimination unit 13 updates the BID, that is, adds +1, and returns to step S451 to process the next record. Note that the discrimination unit 13 may set the result of the discrimination process of the social participation category (steps S456, S457) in the social participation classification table 176. Furthermore, the discrimination unit 13 may specify the social participation category according to the time period. For example, the social participation category can be specified as working by setting the working time period from 9:00 to 17:00 or around this time. Also, the discrimination unit 13 may specify the social participation category directly from the schedule data. This concludes the explanation of FIG. 11, and returns to the explanation of FIG. 7.

[0062] After the above processes of steps S44 and S45, in step S46, the discrimination unit 13 discriminates the social participation category.

[0063] This completes the explanation of FIG. 7, that is, the detailed explanation of step S4. Returning to FIG. 4, the processing from step S5 onwards will be explained.

[0064] In step S5, the index calculation unit 14 calculates a social participation index based on the determined social participation category. The details of this social participation index calculation process will be described with reference to FIG.

[0065] In step S51, the index calculation unit 14 identifies the identified social participation category and the weighting corresponding thereto. To this end, the index calculation unit 14 uses the social participation weight table 177 shown in FIG. 13. That is, the weighting corresponding to the identified social participation category is searched for in the weight table 177. In this way, the social participation category and its weighting are obtained from the social participation classification table 176 and the social participation weighting table 177. The social participation weighting table 177 may be set based on input in the operation management terminals 18-1 and 18-2, or may be set using the results of data analysis of the history data. The weighting is information indicating the weighting for the diversity variable.

[0066] In steps S52 to S55, the index calculation unit 14 calculates a diversity variable that is a variable of the social participation index. The diversity variable is an index that indicates the degree of diversity and complexity of the social activities participated in. The greater the degree of such diversity and complexity, the more active the participants' actions are by using their cognitive stress and judgment abilities, and it can be estimated that the risk of health conditions can be reduced. It is more preferable that the diversity variable is a value according to the involvement status of social activities.

[0067] In step S52, first, the index calculation unit 14 calculates the stay time at the facility in the target behavior history information. To this end, the index calculation unit 14 calculates the difference between the movement start time and the movement end time as the stay time. Then, the index calculation unit 14 specifies the weight, which is one of the diversity variables related to the stay time, from the relationship information between the stay time and the weight, which is one of the diversity variables, stored in advance. An example of the relationship information is shown in FIG. 14 in a graph format. As shown in FIG. 14, the weight increases according to the stay time until the stay time reaches a predetermined value (around 30), and thereafter tends to decrease.

[0068] Also, in step S53, the index calculation unit 14 calculates the diversity of the means of transportation to the facility (for example, transportation means). The diversity of the means of transportation is information indicating the degree of diversity, such as the number and types of means of transportation used by the participant. For this purpose, the index calculation unit 14 may use the number of means of transportation included in the action history information. Then, the index calculation unit 14 specifies the weight, which is one of the diversity variables related to the combination of means of transportation, from the relationship information between the number of combinations of means of transportation stored in advance and the weight, which is one of the diversity variables. Here, an example of the relationship information is shown in a graph format in FIG. 15. As shown in FIG. 15, the weight increases as the number of combinations of means of transportation used by the participant increases, but the degree of increase tends to decrease as the value of the weight increases.

[0069] Furthermore, in step S54, the index calculation unit 14 calculates the number of facilities that are destinations in the series of actions. That is, the number of places in the action history, which is the series of actions in FIG. 8, is counted. At this time, the places are counted by the total number of visits. Then, the index calculation unit 14 identifies the weight, which is one of the diversity variables related to the number of facilities visited by the participant, from the relationship information between the number of facilities visited and the weight, which is one of the diversity variables, stored in advance. Here, an example of the relationship information is shown in FIG. 16 in a graph format. As shown in FIG. 16, the weight increases as the number of facilities visited by the participant increases.

[0070] In step S55, the index calculation unit 14 calculates the number of people at the visited facility, that is, the number of people. For this purpose, it is possible to use a people flow analysis service using location information from a mobile phone company, or the location information 172 or the behavior history information 175. Furthermore, it is also possible to realize this by using a contact app between the mobile terminals 20. In addition, it is also possible to use traffic congestion information and manpower information from a map information service. Then, the index calculation unit 14 specifies the weight, which is one of the diversity variables related to the number of people, from the relationship information between the number of people and the weight, which is one of the diversity variables, stored in advance. Here, an example of the relationship information is shown in FIG. 17 in a graph format. As shown in FIG. 17, the weight increases as the number of people at the visitor's destination increases, but the degree of increase tends to decrease as the weight value increases.

[0071] The order of steps S51 to S55 does not matter, and parallel processing may be performed. At least one of these diversity variables may be calculated. In addition to these, the value of the diversity variable may be increased as the number of facilities visited in the same facility category increases.

[0072] Next, in step S56, the index calculation unit 14 calculates the number of social participations and the social participation index. Note that in this step, the calculation may be limited to the social participation index. In this case, it is preferable to use a social participation index that reflects the number of social participations. For this purpose, the index calculation unit 14 calculates the number of social participations and the social participation index using the behavioral history information, the diversity variable that is the calculation result, the social participation category, and the weight as parameters. As a result, the social participation index and number of times can be specified for each behavioral history and social participation category.

[0073] Then, in step S57, the index calculation unit 14 stores the result of step S56 in the storage device 104 as one piece of social participation analysis data 178. Furthermore, in response to the operation of the operation management terminals 18-1, 18-2, the index calculation unit 14 outputs the result to the operation management terminals 18-1, 18-2. This concludes the explanation of Fig. 12, and we will return to the explanation of Fig. 4.

[0074] Next, in step S6, the incentive value calculation unit 15 calculates an incentive value indicating an incentive for the social participation action provider and the participants, using at least one of the social participation index and the number of social participations calculated in step S5. In this embodiment, the incentive value is calculated as the amount of benefit to the social participation action provider and the number of points to the participants. At this time, the amount of benefit is calculated for each facility (PID), and the number of points is calculated for each participant (UID). The contents of the process will be explained below in the order of (1) the calculation process of the benefit amount, and (2) the calculation process of the number of points.

[0075] First, Fig. 26 is a flow chart showing the calculation process of the benefit amount in this embodiment. In step S601, the incentive value calculation unit 15 sets the PID of the facility that is the subject of the benefit amount (survey target) and the survey period. This may be according to an input from the operation management terminal 18, or the incentive value calculation unit 15 may specify each PID when a predetermined condition such as a predetermined period is satisfied. In this embodiment, the survey is performed once a month.

[0076] Next, in step S602, the incentive value calculation unit 15 performs initial settings for the benefit tally table 180 (BT). That is, the incentive value calculation unit 15 stores the contents set in step S601 in the benefit tally table 180 in which data has not been registered.

[0077] Here, Fig. 28 is a diagram showing the benefit tallying table 180 used in this embodiment. In Fig. 28, the benefit tallying table 180 has the following items: PID, tallying start time, tallying end time, total number of visits, benefit standard, benefit standard amount, new customer, additional benefit amount, and total benefit amount. In this step, the incentive value calculation unit 15 sets each PID set in step S601 to the same item in the benefit tallying table 180. Furthermore, the incentive value calculation unit 15 sets the survey period set in step S601 to the tallying start time and tallying end time. The other items are set in the process described below.

[0078] Next, in step S603, the incentive value calculation unit 15 reads, in an arbitrary order, the PIDs set in the benefit tallying table 180. Then, the following steps are executed for the read PIDs.

[0079] First, in step S604, the incentive value calculation unit 15 reads out the total number of visits of the PID read out in step S603 from the facility-specific tally information table 187 (PT). For the facility with "PID"="1", in the example of FIG. 25, "total number of visits"="5" is read out.

[0080] In step S605, the incentive value calculation unit 15 reads out the facility category of the PID read in step S603 from the facility category table 174 or the POI table 173. For the facility with "PID"="1", in the example of the POI table 173 in Fig. 9A, "facility category"="community center" is read out.

[0081] Next, in step S606, the incentive value calculation unit 15 multiplies the total number of visits read out in step S604 by the social participation weight corresponding to the facility category read out in step S605 to calculate a benefit standard.

[0082] For this purpose, the incentive value calculation unit 15 first identifies a social participation category corresponding to the read facility category by using the social participation classification table 176. In the above example, since "facility category"="community center" is read, in the example of Fig. 10, "social participation category"="hobby (cultural)" is identified.

[0083] Next, the incentive value calculation unit 15 specifies a weight corresponding to the specified social participation category using the social participation weight table 177. In the example of Fig. 13, a "weight" of "1.5" corresponding to the "social participation category" = "Hobbies (cultural)" is specified.

[0084] Then, the incentive value calculation unit 15 multiplies the total number of visits read out by the identified weight. In other words, "total number of visits" = "5" × "weight" = "1.5" is executed, and "7.5" is calculated, and this number is set as the "payment standard."

[0085] Next, in step S607, the incentive value calculation unit 15 stores the calculated payment standard in the payment summary table 180. Furthermore, it is preferable that the incentive value calculation unit 15 stores the total number of visits read out in step S604 in the payment summary table 180. However, the storage of the total number of visits is not limited to being performed in this step.

[0086] In step S608, the incentive value calculation unit 15 identifies participants who visited the facility indicated by the PID read in step S603, that is, who performed social participation behavior. To this end, the incentive value calculation unit 15 identifies and reads out the UID corresponding to the read PID from the facility-specific tabulation information table 187.

[0087] Next, in step S609, incentive value calculation unit 15 identifies participants who have no record of visiting during the previous survey period, i.e., one month ago. To this end, incentive value calculation unit 15 searches benefit summary table 180 created in the previous cycle using the UID read in step S608 as a key. As a result, UIDs that were not searched for are identified. Then, incentive value calculation unit 15 stores at least one of the identified UIDs and their number in the "new customers" field of benefit summary table 180 for this time.

[0088] Next, in step S610, the incentive value calculation unit 15 checks whether there is any PID that has not been read in step S603 among the PIDs set in step S601. If there is any (Y), the process proceeds to step S611. If there is no PID (N), the process proceeds to step S612.

[0089] In step S611, the incentive value calculation unit 15 updates the PID read in step S603. For example, the incentive value calculation unit 15 specifies the PID to be processed next by adding 1 to the read PID. Then, in step S603, the updated PID is read.

[0090] Furthermore, in step S612, the incentive value calculation unit 15 multiplies the benefit standard calculated in step S606 by the benefit unit price to calculate the benefit base amount for the facility of the PID read in step S603. Then, the incentive value calculation unit 15 stores the calculated benefit base amount in the benefit summary table 180. In the example of Fig. 28, the benefit unit price is 10 yen, and for "PID"="1", "benefit base amount"="75 (yen)" is stored.

[0091] Furthermore, in step S613, if there is a new customer at the facility of the PID read in step S603, the incentive value calculation unit 15 calculates an additional benefit amount for the facility. To this end, the incentive value calculation unit 15 multiplies the number of new customers identified in step S609 by a predetermined additional unit price. The incentive value calculation unit 15 then stores this calculation result in the additional benefit amount in the benefit summary table 180. In the example of FIG. 28, for "PID"="1", "new customer"="2"×"100" is used to calculate "additional benefit amount"="200 (yen)", and this is stored.

[0092] Then, in step S614, the incentive value calculation unit 15 calculates the sum of the benefit base amount calculated in step S612 and the additional benefit amount calculated in step S613 as the total benefit amount for the facility of the PID read in step S603. The incentive value calculation unit 15 then stores this calculation result in the total benefit amount in the benefit summary table 180. In the example of FIG. 28, for "PID"="1", "benefit base amount"="75 (yen)" + "additional benefit base amount"="200 (yen)" results in "total benefit amount"="275 (yen)" being stored. This total benefit amount becomes the benefit amount for the facility in question.

[0093] This is the end of this flow, but although this flow is an example in which the benefit unit price is a uniform 10 yen, other calculation methods can also be used in this embodiment. Other examples will be described below.

[0094] Fig. 27 is a diagram showing a benefit management table 179 used in this embodiment to explain another calculation method. The benefit management table 179 is a table showing the benefit standard for each PID, that is, for each facility. For this reason, in Fig. 27, the benefit management table 179 is provided with the facility name, address, parent facility PID, facility category, benefit rate, benefit unit price, and additional unit price for each PID.

[0095] Here, since residential facilities are not visited as part of social participation, a value of "0" is set. The benefit multiplier, benefit unit price, and additional unit price are set for each PID, i.e., for each facility, but may also be set for each facility category.

[0096] Incidentally, including the above example, the additional unit price indicates the unit price to be added in the case of a facility that is not visited continuously. Here, since "employment" in the "social participation category" is usually a periodic activity, it is set not to be added in this embodiment. Therefore, when the "social participation category" corresponding to the "facility category" in step S605 is "employment", the incentive value calculation unit 15 may skip steps S609 and S613.

[0097] The processing contents of the other calculation methods will be described below. In step S606, the incentive value calculation unit 15 specifies the payout rate corresponding to the PID read in step S603 from the payout management table 179 and uses this. Similarly, in step S612, the incentive value calculation unit 15 specifies the payout unit price corresponding to the read PID from the payout management table 179 and uses this. In addition, in step S613, the incentive value calculation unit 15 specifies the additional unit price corresponding to the read PID from the payout management table 179 and uses this. Furthermore, in step S605, the incentive value calculation unit 15 may specify a facility category using the payout management table 179.

[0098] This concludes the explanation of (1) the payment amount calculation process, and the following will explain (2) the point calculation process. Fig. 29 is a flowchart showing the point calculation process in this embodiment.

[0099] First, in step S615, the incentive value calculation unit 15 sets the UID of the participant who is the subject of the payment amount (survey target), the survey period, and the PID of the facility. This may be according to input from the operation management terminal 18, or the incentive value calculation unit 15 may specify each UID and PID when a predetermined condition such as a predetermined period is satisfied. In this embodiment, the survey is performed once a month. Furthermore, in this embodiment, the calculation process of the payment amount and the calculation process of the points are performed independently, so the survey period and PID are also set in this flow. However, the survey period and PID may be reused from the contents set in the calculation process of the payment amount.

[0100] Next, in step S616, the incentive value calculation unit 15 performs initial settings for the point tallying table 182 (AT). That is, the incentive value calculation unit 15 stores the contents set in step S615 in the point tallying table 182 where no data has been registered.

[0101] FIG. 31 is a diagram showing the point tally table 182 used in this embodiment. 31, point tally table 182 has the following items: UID, tally start time, tally end time, base points, base point count, number of new visits, number of additional points, and total payment amount. In this step, incentive value calculation unit 15 sets each UID set in step S615 to the same item in point tally table 182. Furthermore, incentive value calculation unit 15 sets the survey period set in step S615 to the tally start time and tally end time. The other items are set in the process described below.

[0102] Next, in step S617, the incentive value calculation unit 15 reads, in an arbitrary order, the UIDs set in the point tallying table 182. Then, the following steps are executed for the read UIDs.

[0103] First, in step S618, the incentive value calculation unit 15 reads out the number (N) of PIDs corresponding to the UID read out in step S617 from the person-specific tally information table 188 (UT). That is, the incentive value calculation unit 15 counts the number of facilities visited by the participant with the read out UID. Then, the incentive value calculation unit 15 substitutes the read out N for n set out in step S615.

[0104] Next, in step S619, the incentive value calculation unit 15 judges whether n is 0. As a result, if n is not 0 (N), the process proceeds to step S620. If n is 0 (Y), the process proceeds to step S625.

[0105] In step S620, the incentive value calculation unit 15 identifies a PID that has not executed the following process among the PIDs corresponding to the UID read in step S617. The incentive value calculation unit 15 then reads out the facility category of the identified PID. This reading can be performed in the same manner as in step S605.

[0106] In step S621, the incentive value calculation unit 15 calculates the reference points by multiplying the total number of visitors to the specified PID by the weight of social participation corresponding to the facility category read out in step S620. Here, the total number of visitors to the specified PID is the total number of visitors in the person-specific total information table 188.

[0107] Next, in step S622, incentive value calculation unit 15 stores the calculated reference points in point tally table 182 in association with the read UID. This step is included in the repetitive process, and if a value has already been stored in point tally table 182, the calculated value is added to the stored value.

[0108] In step S623, the incentive value calculation unit 15 identifies the PID corresponding to the UID set in step S617 from the facility-specific tabulation information table 187 and reads it out. In response to this, in step S624, the incentive value calculation unit 15 determines whether there is a record of a visit to the read PID during the previous survey period, that is, one month ago. This determination can be realized by the same process as in step S609. If there is no record of a visit, the incentive value calculation unit 15 adds 1 to the number of new visits for the corresponding PID in the facility-specific tabulation information table 187.

[0109] Next, in step S625, the incentive value calculation unit 15 adds 1 to n, and the process proceeds to step S619.

[0110] In step S626, the incentive value calculation unit 15 checks whether there is any UID that has not been read in step S617. If there is any UID (Y), the process proceeds to step S627. If there is no UID (N), the process proceeds to step S628.

[0111] In step S627, the incentive value calculation unit 15 updates the UID read in step S617. For example, the incentive value calculation unit 15 adds 1 to the read UID to identify the UID to be processed next. Then, in step S617, the updated UID is read.

[0112] In step S628, the incentive value calculation unit 15 multiplies the reference points calculated in step S621 by the point unit price (for example, 10) to calculate the reference point number for the participant whose UID was read in step S617. At this time, the incentive value calculation unit 15 stores the reference point number in the point tally table 182 in correspondence with the read UID.

[0113] Furthermore, in step S629, incentive value calculation unit 15 determines whether there is a record of a visit for the read UID during the previous survey period, i.e., one month ago. For this purpose, in this step, the same process as in step S609 is executed. Then, incentive value calculation unit 15 identifies the number of new visits for the read UID, and multiplies this by the points used to calculate the number of additional points for the participant of the read UID. At this time, incentive value calculation unit 15 stores the number of additional points in point tally table 182 in correspondence with the read UID.

[0114] Next, in step S630, incentive value calculation unit 15 calculates the sum of the reference points calculated in step S628 and the additional points calculated in step S629 as the total points. At this time, incentive value calculation unit 15 stores the total points in point tally table 182 in association with the read UID. This is the end of this flow, and although this flow shows an example in which the point unit price is a uniform 10 (points), other calculation methods can also be used in this embodiment. Other examples will be described below.

[0115] Fig. 30 is a diagram showing a point management table 181 used in this embodiment to explain another calculation method. The point management table 181 is a table showing the point criteria for each PID, that is, for each facility. Therefore, in Fig. 30, the point management table 181 has, for each PID, its registration time, facility name, address, parent facility PID, facility category, point multiplier, point unit price, and additional points.

[0116] Here, as with the benefit management table 179, since residential facilities are not visited as part of social participation, "0" is set. Also, the point multiplier, point unit price, and additional points are set for each PID, i.e., for each facility, but may also be set for each facility category.

[0117] Incidentally, including the above example, the additional points indicate the unit price to be added in the case of facilities that are not visited continuously. Here, since "employment" in the "social participation category" is usually a periodic activity, it is set not to be added in this embodiment. When the "social participation category" is "employment", the incentive value calculation unit 15 may skip steps S629 and S630.

[0118] The processing contents of the other calculation methods will be described below. In step S628, incentive value calculation unit 15 identifies the point magnification corresponding to the UID read in step S617 from point management table 181 and uses this. Similarly, incentive value calculation unit 15 identifies the point unit price corresponding to the read UID from point management table 181 and uses this. In step S629, incentive value calculation unit 15 identifies the additional points corresponding to the read UID from point management table 181 and uses this. For example, the calculation of the reference point "20.1" for UID=1 in the point tallying table 182 and the start time of the meeting=2021.01.01 00:00:00:00 is performed as 5×1.5+9×1.4=20.1 from the values ​​of 5 visits to PID=1 and 9 visits to PID=2, which are the corresponding visit destinations in the person-specific tallying information table 188, and the point multipliers of 1.5 for PID=1 and 1.4 for PID=2 in the point management table 181. Furthermore, in step S621, the incentive value calculation unit 15 may specify the facility category using the point management table 181.

[0119] As shown in this embodiment, the system is configured to automatically calculate and determine the amount of benefits to facilities that cooperate in promoting social participation and the number of points to participants according to the number of visits to the facilities by the participants. In addition, when a facility that was not visited in the previous month is visited, additional benefits and additional points are automatically added, so that the amount of benefits and points are added according to the frequency of visits. Furthermore, the amount of benefits and the number of points can be weighted according to the social participation category. In addition, the grant rate or addition of benefits and points is not applied to visits to special facilities such as visits to homes and employment facilities, or can be set to a different value. Therefore, a remarkable effect is obtained in that a high incentive can be automatically given to social participation that is more beneficial for preventing dementia and the need for care. In addition, a remarkable effect is obtained in that participants and facilities can select actions and facility operations that promote social participation that are more beneficial for preventing dementia and the need for care. Furthermore, an excellent effect is obtained in that incentives corresponding to various forms such as profit-making organizations and non-profit organizations can be automatically calculated and given, which is difficult to achieve by point allocation linked to the facility's advertising revenue or sales revenue.

[0120] Now that the explanation of the alternative calculation method is finished, the GUI (Graphical User Interface) in this embodiment will be explained. Fig. 32 is a diagram showing a display screen on the provider management terminal in this embodiment. In Fig. 32, the number of visits and the amount of benefits for the relevant facility are displayed. Specifically, (a) displays the total number of participants and the number of new participants at the relevant facility. Also, (b) displays the average total number of visitors and the average number of visitors at the relevant facility. Furthermore, (c) displays the total amount of benefits for the relevant facility. Note that (a) to (c) may be displayed on separate screens, or may be displayed together.

[0121] The details of each display content will be explained below. The total number of participants in (a) is specified by the data analysis unit 16 counting the number of UIDs corresponding to the relevant PID among the UIDs in the facility-specific additional information 185. The number of new participants is specified by the data analysis unit 16 counting the number of new customers in the benefit summary table 180 that correspond to the relevant PID. The data analysis unit 16 then outputs the counting result to the provider management terminal or its data utilization system via the output unit 12. As a result, the provider management terminal displays the contents of (a). This display may be executed independently of the steps in FIG. 26 or FIG. 29, or may be executed when these steps are completed.

[0122] Here, the facility-specific additional information 185 will be described. FIG. 36 is a diagram showing the facility-specific additional information 185 used in this embodiment. The facility-specific additional information 185 is information showing the characteristics of each facility. Specifically, as shown in FIG. 36, the facility-specific additional information 185 records, for each PID, the registration time of the facility, the facility name, the address, the parent facility PID, the facility category, the destination exclusion, the business day setting, and the business hour setting. Here, the destination exclusion is a flag indicating whether to exclude the facility during a search, and if 1 is recorded, the facility is excluded from the search target when determining the priority order described later. For example, it is possible to exclude large-scale commercial facilities that are difficult to identify as residential facilities, working facilities, and visiting facilities.

[0123] Moreover, the average total number of visitors in (b) is calculated by the data analysis unit 16 dividing the total number of visitors in the corresponding PID in the facility-specific additional information 185 by the survey period or the like. As a result, the average total number of visitors in each unit period (e.g., one day) in the facility is calculated. Moreover, the data analysis unit 16 calculates the average number of visitors by excluding duplicates from the average total number of visitors. The data analysis unit 16 then outputs the counting result to the provider management terminal or its data utilization system via the output unit 12. As a result, the provider management terminal displays the contents of (b). Note that this display may be synchronized with the timing of the display of (a) described above.

[0124] Furthermore, for the total benefit amount for the facility in question in (c), the incentive value calculation unit 15 uses the total benefit amount calculated in step S614. The incentive value calculation unit 15 then outputs this to the provider management terminal or its data utilization system via the output unit 12. As a result, the provider management terminal displays the contents of (c). This display may be synchronized with the timing of the displays of (a) and (b) described above. Furthermore, in addition to the display as shown in FIG. 32, information indicating the facility and the benefit amount may also be displayed on the map. Furthermore, these displays may be performed by the operation management terminal 18.

[0125] As shown in this embodiment, the utilization status of participants in a facility that cooperates in promoting social participation, the increase in the number of new participants, the average number of visitors per day, the average number of visitors, and the amount of benefits are automatically calculated, including changes over time and the correlation between each piece of information, so that the facility manager can objectively grasp them. Therefore, the manager can grasp the degree of contribution to the promotion of local social participation and its trends, such as whether the number of new participants is increasing, and how many participants are repeat visitors based on the difference between the average number of visitors and the average number of visitors, and has the remarkable effect of being able to objectively appeal to the facility's staff and visitors to the facility, or to the facility's local residents and government, etc. Furthermore, it has the excellent effect of being able to accurately grasp the increase or decrease in the amount of benefits to be obtained.

[0126] This concludes the explanation of the display screen on the provider management terminal.

[0127] Next, FIG. 33 is a diagram showing a display screen on the mobile terminal 20 in this embodiment. Here, FIG. 33 shows the contents of the notification to each participant when the number of points is calculated. The display screen in FIG. 33 includes an overview area 33-1 and a detailed area 33-2. The overview area 33-1 shows an overview of the facilities related to the participant. In this embodiment, the visited facilities and the proposed facilities (black circles in the figure) proposed by the system are mapped on the map as related facilities. In addition, the detailed area 33-2 displays the proposed facilities and their contents in the order of priority of the proposal. These display contents are created by the data analysis unit 16 as follows. Then, these are output to the mobile terminal 20 via the output unit 12.

[0128] First, the data analysis unit 16 identifies the PID of the visit destination of the relevant participant from the person-specific total information table 188. Next, the data analysis unit 16 identifies the UID of the other participant who is visiting the facility indicated by the identified PID. Next, the data analysis unit 16 identifies the facility visited by the participant from the person-specific total information table 188 using the UID of the identified other participant. For example, if the relevant participant is visiting the XX Community Center, the data analysis unit 16 identifies the facilities frequently visited by the other participants who are visiting the XX Community Center in descending order of the number of visitors. As a result, the top (predetermined number) of the identified facilities are superimposed on the map information stored in advance by the behavior analysis device 10 or stored in the map server, and displayed in the overview area 33-1. Furthermore, the detailed area 33-2 is displayed for the facilities displayed in the overview area 33-1.

[0129] The data analysis unit 16 also uses the point management table 181 to identify the points of the facilities visited by other participants. Also, using the person-specific tally information table 188, it is determined whether the facility is a new visit destination for the participant, that is, whether the visit destination is a target for acquiring additional points. As a result, the number of points that can be obtained when visiting the facility (for facilities where additional points can be acquired, "100 points bonus") is displayed. Then, the data analysis unit 16 presents each of the identified points in the corresponding area in the detailed area 33-2 via the output unit 12. Furthermore, the detailed area 33-2 displays a catchphrase and a route guidance button for each facility. Here, when the route guidance button is clicked, the navigation function of the mobile terminal 20 is activated, and a route from the location of the currently visited facility to the facility is displayed. It is preferable to exclude the facility displayed in FIG. 33 from the display when it is outside business hours or on a holiday. Furthermore, some of the above-mentioned display items may not be displayed.

[0130] Here, the calculation of the average total number of visitors and the average number of visitors in FIG. 32(b) and the specification of the priority order in the detailed area 33-2 in FIG. 33 will be described.

[0131] First, the average total number of visitors will be explained. Fig. 34 is a diagram showing the total number of visitors calculation table 183 used in this embodiment. The total number of visitors calculation table 183 is configured in a matrix, and the total number of visitors to each facility (PID) in a certain period (for example, one month) is stored on both axes. For this reason, Fig. 34 shows that the visitors to the community center with "PID" = "1" are more numerous than those with "PID" = "7", "6", and "2", in that order. Also, the column with the same PID on both axes shows the total number of visitors to that facility.

[0132] Therefore, the data analysis unit 16 calculates the column with the same PID on both axes as the total number of visitors to the facility. The data analysis unit 16 also specifies the above order (7, 6, 2) as the priority order of the detailed area 33-2. The home column with "PID" = "0" indicates the number of times the participant went out.

[0133] Next, the average number of visitors will be explained. If the priority order is determined by the total number of visitors, facilities that are used frequently (number of visitors) due to daily use, such as grocery stores, may consistently be ranked higher. Therefore, it is possible to use the average number of visitors instead of the above-mentioned average total number of visitors. The details of this will be explained below.

[0134] Fig. 35 is a diagram showing the visitor count calculation table 184 used in this embodiment. The visitor count calculation table 184 stores the number of visitors to each facility (PID) in a certain period (e.g., one month) on both axes of a matrix. In the example of Fig. 35, the other facilities most frequently visited by visitors to the community center with "PID" = "1" are "PID" = "7", "6", and "5", in that order. Thus, compared to when the average total number of visitors is used, the third facility has changed from 2 to 5.

[0135] Therefore, the data analysis unit 16 calculates the number of visitors to the facility in question for the column with the same PID on both axes. The data analysis unit 16 also specifies the above-mentioned order (7, 6, 5) as the priority order for the detailed area 33-2. This is because the facility with "PID" = "2" is a facility that is visited on a daily basis, and lowering its order can lead to an encouragement to promote social participation by increasing the number of places visited.

[0136] The data analysis unit 16 calculates the number of visitors to the facility in question for the column in which the PIDs on both axes are the same. The data analysis unit 16 also specifies the above order (7, 6, 5) as the priority order for the detailed area 33-2.

[0137] As shown in this embodiment, the participant can check candidates for destinations that can be reached from the current location using the navigation function of the mobile device. In addition, the total visitor number calculation table or the visitor number calculation table can automatically calculate the destinations that are frequently visited by visitors to the facility currently visited by the participant, and present them as candidates for new destinations recommended to the participant. In addition, if the destination is outside business hours or on a holiday, it is not automatically displayed as a candidate. Furthermore, the number of points that the participant can earn when visiting the destination presented as a candidate is automatically calculated and presented, including the number of additional points, using the point management table and the participant's past social participation behavior history. Therefore, a remarkable effect is obtained in that the participant can easily select a facility that the participant himself can visit and that leads to the promotion of social participation that is more beneficial for the prevention of dementia and the need for care from the map, depending on the current location and the date and time of stay. Furthermore, since the participant can simultaneously grasp the incentive that is given higher for social participation that is more beneficial for the prevention of dementia and the need for care, it is possible to encourage the participant to take action to select more effective social participation, and it is possible to naturally support behavioral change that leads to the promotion of more social participation, which is an extremely excellent effect.

[0138] This concludes the description of the calculation of the average total number of visitors and the average number of visitors, and the specification of the priority order of the detailed area 33-2 in this embodiment.

[0139] Next, the process of determining the point unit price in this embodiment will be described. The point unit price is used in the calculation of the reference point number in step S628 described above. Figure 37 is a flowchart showing the process of determining the point unit price in this embodiment.

[0140] First, in step S631, the incentive value calculation unit 15 estimates the total number of points (P-all) for the year using the point tally table 182. At this time, the incentive value calculation unit 15 estimates P-all based on the total number of points granted in a certain period (e.g., one month) in the point tally table 182. An example of this estimation will be described with reference to FIG.

[0141] Fig. 38 is a diagram for explaining a method for estimating the total number of points (P-all) for a year in this embodiment. Fig. 38(a) is a graph showing the total number of points (accumulated value for April) for one month (April) in the point tallying table 182. Also, (b) is a graph showing the annual flow of people, i.e., the number of people leaving the service area (such as area A in Fig. 1). The flow of people in the service area in (b) can be calculated, for example, from the number of people entering and leaving the area where the participants live, using the location information of the mobile terminal 20.

[0142] Here, the social participation of people increases or decreases in proportion to the flow of people. For this reason, it is considered that the distribution points also change according to the flow of people. Therefore, in (c), the incentive value calculation unit 15 extrapolates the total point value for one month (a) according to the fluctuation of the flow of people (b). In other words, the tendency of fluctuation of the annual flow of people is applied to the total point value for one month (April). As a result, in (d), the incentive value calculation unit 15 estimates the extrapolated cumulative value for the year as the total number of points for the year. This concludes the explanation of the method for estimating the total number of points for the year (P-all), and we will return to the explanation of FIG. 37.

[0143] In step S632, the incentive value calculation unit 15 determines the total annual contribution amount (R-all) from related parties such as participants and social participation action providers. To this end, the incentive value calculation unit 15 uses the contribution amount of each related party stored in advance.

[0144] Next, in step S633, the incentive value calculation unit 15 sets the point unit price, which is the total investment amount (R-all) divided by the total number of points (P-all). This point unit price may be used continuously, but it is considered that the number of points given may deviate from the estimated total number of points (P-all) depending on the state of social participation behavior. In other words, it is considered that the total investment amount, which is the source of funds, may become insufficient or excessive. Therefore, in this embodiment, steps S631 to S633 are set as the initial value of the point unit price, and in the following steps, the point unit price is changed according to the actual situation. In addition, it is preferable to set this point unit price for each unit period having a plurality of the above-mentioned fixed periods such as a fiscal year or a year. In particular, it is preferable to set it when the unit period starts (for example, April).

[0145] For a fixed period such as one month, that is, in step S634, the incentive value calculation unit 15 performs the process of FIG. 29 using the point unit price set in step S633. In other words, for the fixed period, the operation of calculating the number of points is executed at the initial point unit price. Then, in step S635, the incentive value calculation unit 15 judges whether the above-mentioned fixed period has elapsed. As a result, if the period has not elapsed (N), the process returns to step S634 and continues. On the other hand, if the period has elapsed (Y), the process transitions to step S636.

[0146] In step S636, the incentive value calculation unit 15 specifies the number of points granted in the above-mentioned fixed period, that is, the number of points calculated by the incentive value calculation unit 15. To this end, the incentive value calculation unit 15 adds up the total number of points in the fixed period determined by the tally start time or tally end time in the point tally table 182.

[0147] Next, in step S637, the incentive value calculation unit 15 calculates the product of multiplying the total number of points from the beginning of the fiscal year or year to the relevant period (for example, the current month) by the point unit price set in step S633. This identifies the amount indicated by the total number of points already granted. Hereinafter, this amount will be referred to as the distributed amount.

[0148] Furthermore, in step S638, the incentive value calculation unit 15 estimates the estimated total number of points, which is the total number of points for the remaining period within a unit period after the relevant period (for example, the current month). Then, the incentive value calculation unit 15 calculates the product of multiplying the estimated total number of points by the point unit price set in step S633. In this way, the amount indicated by the total number of points to be awarded is specified. Hereinafter, this is referred to as the remaining distribution amount. Note that the incentive value calculation unit 15 can estimate the estimated total number of points from the tendency of the participants to go out for a certain period (for example, monthly).

[0149] Next, in step S639, the incentive value calculation unit 15 compares the sum of the distributed amount and the remaining distributed amount with the total investment amount (R-all) determined in step S632. As a result, if the sum of the distributed amount and the remaining distributed amount is greater (Y), the process proceeds to step S640. Also, if the total investment amount (R-all) is greater (N), the process proceeds to step S642. As a result, the point unit price set as the initial value in step S633 is corrected. In this step, the progress toward the total investment amount (R-all), which is the annual budget, is confirmed. Then, in the following steps, the point unit price is corrected by lowering the point unit price if the budget is likely to be exceeded, or by raising the point unit price for a certain period of time if the budget is likely to be exceeded.

[0150] If these values ​​are the same or the difference is within a certain range, the process ends at this step and the initial value is used as the point unit price. Alternatively, the process may be controlled to transition to either step S640 or S642. In this case, it is assumed that the transition destination will be determined according to the usage policy of the total investment amount, for example, to use it with a margin.

[0151] First, in step S640, the incentive value calculation unit 15 calculates (total investment amount (R-all) - distributed amount) / estimated total number of points to calculate a revised point unit price. This may be used as a new point unit price, but in this embodiment, further revision is made. That is, in step S641, the incentive value calculation unit 15 makes a downward revision of the calculated revised point unit price, such as by reducing it by a specified value or a specified percentage. As described above, the revised point unit price may be used as is, or the downwardly revised value may be used.

[0152] Also, in step S642, as in step S640, the incentive value calculation unit 15 calculates (total investment (R-all)-distributed amount) / estimated total number of points, and calculates the corrected point unit price. Note that, as in step S640, this may be used as a new point unit price, but in this embodiment, further correction is performed. That is, in step S644, the incentive value calculation unit 15 performs an upward correction on the calculated corrected point unit price with respect to the initial value. For this purpose, the incentive value calculation unit 15 increases the initial value by a predetermined value or a predetermined percentage. Note that, as described above, the corrected point unit price may be used as it is, or the upwardly corrected value may be used. Also, in this embodiment, steps S640 and S642 are performed after step S639, but this order can be changed. That is, after the calculation of the corrected points, the sum may be compared with the total investment (R-all).

[0153] Then, in step S644, the incentive value calculation unit 15 determines the corrected unit point corrected in steps S641 to S643 as the point unit price. The determined point unit price is set in the point management table 181 or the like.

[0154] As shown in this embodiment, the point unit price is adjusted so as not to exceed the total investment amount, which is the operating capital of the service. In addition, the total number of points per year can be estimated using other information related to social participation, such as the annual flow of people. In addition, the remaining amount of distribution is estimated at the time when a certain period (for example, one month) has passed, and the point unit price is adjusted so that the sum of the distributed amount and the remaining amount of distribution does not exceed the total investment amount. Alternatively, a point unit price that relates the reference point and the reference number of points is used, and the number of points to be granted to participants can be easily adjusted according to the point unit price. Therefore, there is a remarkable effect that it is possible to operate a sustainable service that avoids operating deficits according to the point distribution performance. Furthermore, there is a remarkable effect that the total number of points per year can be estimated more accurately than when it is estimated simply from the number of days of service operation, or can be estimated more accurately even if there is no operating performance of the social participation service. In addition, even if the external environment changes significantly during the year, such as a change in social conditions or the onset of an infectious disease, a very excellent effect is obtained in that a more appropriate adjustment of the point unit price can be realized.

[0155] In this embodiment, the method of adjusting the unit price of points given to participants so as not to exceed the total investment amount has been described, but the total amount of benefits paid to the facility can also be adjusted by adjusting the unit price of benefits using a similar procedure. Alternatively, it is possible to adjust both of them so that the operating capital of the service does not exceed the total investment amount, which is the operating capital of the service, by points and benefits. For example, the division ratio of points distributed to participants and distribution to the facility with respect to the total investment amount is determined in advance, and the unit price of points and the unit price of benefits are adjusted so that they fall within the range of the divided investment amount. Then, taking into account the satisfaction of the participants and the satisfaction of the facility with respect to the incentive distribution, the division ratio of the distribution amount is corrected, and the unit price of points and the unit price of benefits can be adjusted again according to the divided investment amount after the correction. Compared to the case where only the unit price of points given to participants is adjusted, a wonderful effect is obtained in that a more sustainable service can be operated, including the implementation status and satisfaction of the facility's efforts regarding the service.

[0156] This concludes the explanation of the point unit price determination process of this embodiment.

[0157] Returning to the explanation of FIG. 4, the processing contents will be explained below.

[0158] In step S6, the calculation of the number of points may be performed by the point operating company system 60. For this purpose, the incentive value calculation unit 15 transmits the social participation index and the number of social participation times for each participant (UID) to the point operating company system 60 via the output unit 12. In order to protect the privacy of the participants, a separate index obtained by converting the social participation index and the number of social participation times may be transmitted, or the social participation index and the number of social participation times may be encrypted or anonymized before transmission.

[0159] Then, the incentive value calculation unit 15 accumulates the social participation index, the number of social participations, and the points in the participant information 171.

[0160] Next, in step S8, the mobile terminal 20 reads out and displays the social participation index, the number of social participations, and the points from the behavior analysis device 10 in response to the operation of the participant. However, this display may be push-distributed from the behavior analysis device 10, triggered by the accumulation in step S7. Furthermore, a terminal device such as a PC used by a participant other than the mobile terminal 20 may execute step S8. Furthermore, it is preferable that the social participation index and the number of social participations can also be displayed on the operation management terminals 18-1 and 18-2 and the administrative agency terminals 72-1 and 72-2. In this case, it is preferable to display the information excluding information that identifies individuals, such as names, from the viewpoint of privacy protection. Note that the social participation index and points displayed on the mobile terminal 20 are limited to those of the corresponding participant.

[0161] The display contents in step S8 are shown in Figs. 18 and 19. Fig. 18 is a display example (part 1) of the social participation index or the number of times of social participation. As shown in Fig. 18, the display contents are shown in the form of a graph showing the values ​​of each social participation category. The average for the region, which is an example of that environment, is also shown. The numerical values ​​for each social participation category indicate values ​​or average values ​​for a certain period of time, such as one week or one month. It is also preferable that the overall evaluation is an average value obtained by weighting the values ​​of each social participation category.

[0162] Furthermore, the change over a certain period of time immediately prior may be displayed, or the cumulative value from the start of participation in this service may be displayed, or a comparison may be made with participants of the same attributes, such as the same sex / age, in the same area. Furthermore, a combination of these may be displayed. Furthermore, both the social participation index and the number of social participations may be displayed.

[0163] Next, FIG. 19 is a display example (part 2) of the social participation index or the number of times of social participation. The difference from FIG. 18 is that "employment" is excluded from the social participation categories. This is because the presence or absence of employment has a large impact on the social participation index and the number of times of social participation, and getting a new job is not easy compared to other social participation categories, so the display of this category is made selectable. Here, "selectable" may mean switching by the operation of the operator of the mobile terminal 20 or the operation management terminals 18-1, 18-2, or selectable as a function of the behavior analysis device 10. In particular, in the latter case, if the participant information 171 includes information on the place of employment (such as the name of the facility where the person works), it is desirable that the contents of FIG. 18 be displayed, and if not, the contents of FIG. 19 be displayed.

[0164] Then, in step S9, the mobile terminal 20 uses the point application to enable the points to be used.

[0165] In step S10, the data analysis unit 16 judges whether the analysis conditions are met. In other words, it judges whether the time for analysis has come or whether a data analysis instruction has been received from the operation management terminals 18-1 and 18-2 or the administrative agency terminals 72-1 and 72-2. If the conditions are not met (N), the process returns to step S3. If the conditions are met (Y), the process proceeds to step S11.

[0166] Next, in step S11, the data analysis unit 16 performs data analysis on the health condition using various information. Then, in step S12, the data analysis unit 16 outputs the results to the operation management terminals 18-1, 18-2 or the administrative agency terminals 72-1, 72-2 (hereinafter simply referred to as administrative agency terminals 72) via the output unit 12. Note that, although the administrative agency terminal 72 is used in this embodiment, the results may be output to another data utilization system.

[0167] Next, in step S13, the administrative agency terminal 72 displays the analysis results. Then, in step S14, support for the formulation of various policies is provided in the administrative agency system 70 or other data utilization systems in accordance with the analysis results and the operator's input.

[0168] As described above, in this embodiment, the social participation index weighted as shown in FIG. 13 according to the procedure shown in FIG. 12 in accordance with the social participation category shown in FIG. 10 can be calculated and displayed. Furthermore, as shown in FIG. 14 to FIG. 16, various weightings can be performed according to the duration of stay, the diversity of means of transportation, going out to multiple facilities, the number of people staying at the facility visited, and the like. This makes it possible to deal with the fact that the impact of social participation on nursing care prevention varies depending on not only the place of social participation but also the type (category) of social participation behavior such as employment, hobby club, sports club, volunteer group, shopping, and work, which affects the degree of suppression of nursing care support. In addition, it is possible to solve the problem that there are various influences related to the degree of suppression of nursing care support for social participation behavior, such as the duration of stay at the visit destination according to the type of activity, the diversity (complexity) of behavior such as the route to the destination and the type and number of facilities visited at the same time, and the frequency of contact with people at the visit destination. With the above configuration, a remarkable effect can be obtained.

[0169] In addition, as shown in Figures 18 and 19, it is possible to simultaneously compare and display the social participation index as an overall evaluation and the number of social participations by social participation category. Therefore, it is difficult for participants, especially elderly people, to understand all the complex factors, and this has the wonderful effect of solving the problem of needing a method of presenting information that allows them to understand both the overall index and the areas for improvement in social participation behavior.

[0170] Furthermore, by carrying out the above-described processing, in this embodiment, it becomes possible for an institution or the like to carry out various data analyses as described below and to grasp the social participation behavior of participants.

[0171] Here, steps S11 to S13 will be explained again using five analysis methods as examples. Data Analysis (1) As data analysis (1), data analysis for grasping the usage status of each facility will be described. FIG. 20 is a flowchart showing the processing of data analysis (1). This flowchart is executed for each facility, that is, for each PID. In step S101, the data analysis unit 16 sets the PID, period, and participants of the target facility. This may be specified by accepting a designation from the administrative agency terminal 72, or may be set by applying a predetermined rule. Note that, in this case, the target participants can be multiple participants, such as residents of an arbitrary area.

[0172] Next, in step S102, the data analysis unit 16 sets initial settings, for example 0, for UID, BID, Nv, and Nu, which will be processed below. Here, Nv and Nu will be explained. Nv indicates the total number of visits, which indicates the total number of users who used the facility. Therefore, the total number of visits is the sum of the total number of visits of each participant. Nv can then be used as the number of social participations, and the social participation index can be calculated based on this. Furthermore, Nu is the actual number of users of the facility. In other words, it indicates the number of people without counting the same person twice.

[0173] Next, in steps S103 to S111, the data analysis unit 16 counts the number of behavior history information 175 (records) that match the target PID and UID. The results are the total number of times the facility was used and the actual number of users. These are included in the social participation analysis data 178. Each step of the process will be explained below.

[0174] First, in step S103, the data analysis unit 16 reads out a predetermined record from the behavior history information 175 from the database 17. Next, in step S104, the data analysis unit 16 judges whether the read out behavior history information 175 matches the condition set in step S101. Specifically, it is judged whether it is included in the movement start time and movement end time of the read out behavior history information. At this time, it may be judged based on whether either one is included in the investigation period. It is also judged whether both the PID and UID match. If they match (Y), the process proceeds to step S105. If they do not match (N), the process proceeds to step S106.

[0175] Next, in step S105, data analysis unit 16 increments Nv, which was set in step S102, that is, the current target, by +1. Then, in step S106, data analysis unit 16 determines whether the UID set in step S102, that is, the current target, is the first value in this flow. As a result, if it is the first UID (Y), the process proceeds to step S107. If it is not the first UID (N), the process proceeds to step S108.

[0176] Next, in step S107, the data analysis unit 16 increments Nu, which was set in step S102, that is, the current target, by +1. Then, in step S108, the data analysis unit 16 determines whether there is any unread behavior history information 175 (record). As a result, if there is (Y), the process proceeds to step S109. If there is not (N), the process proceeds to step S110.

[0177] Next, in step S109, the data analysis unit 16 updates the BID set in step S102, i.e., the current target BID. To this end, the data analysis unit 16 identifies, for example, a BID that identifies the next behavior from among the read behavior history information. Then, the process returns to step S103.

[0178] Also, in step S110, data analysis unit 16 determines whether there are other target UIDs. As a result, if there are other UIDs (Y), the process proceeds to step S111. On the other hand, if there are no other UIDs (N), the process proceeds to step S112.

[0179] Next, in step S111, the data analysis unit 16 updates the target UID, and the process proceeds to step S103.

[0180] In step S112, the data analysis unit 16 displays the analysis results Nv and Nu on the administrative agency terminal 72 via the output unit 12. The contents of this display are shown in FIG. 21. FIG. 21(a) displays the analysis results in a pie chart for each facility. Here, the size of the pie chart indicates the social participation index and the number of social participations of the facility. Also, the density of the pie chart indicates the number of social participants of the facility. Here, it is preferable that the data analysis unit 16 reflects the calculation results in steps S52 and S55 on the social participation index. That is, adjustments may be made based on the stay time at the facility and the number of people staying at the facility. Furthermore, it is preferable that the social participation index reflects the calculation results in steps S53 and S54. That is, the social participation index of the transit facility (transport facility, other facility) to the facility is adjusted based on the social participation index of the facility. Conversely, the social participation index of the facility may be adjusted based on the social participation index of the transit facility. In this way, the social participation index of the transit facility and the facility that is the destination may be distributed.

[0181] Also, when the operator specifies the pie chart in FIG. 21(a), the display changes to FIG. 21(b). FIG. 21(b) displays the specified pie chart, that is, the social participation index and the number of social participants for each date and time at the facility. The graph is not limited to a circular display, and may be displayed in a form of size, length, etc. according to the social participation index or the number of social participants. According to this data analysis (1), the usage status of each facility, that is, the status of social participation behavior for each facility, can be grasped. Therefore, it is possible to grasp the degree to which each facility contributes to the activation of social participation of local residents. Alternatively, since it is possible to grasp the change over time in the social participation index and the number of social participants, it is possible to quantitatively grasp the effect that measures such as the establishment or improvement of facilities or the holding of new social participation events have had on social participation. In addition, since the number of social participants and the social participation index are displayed at the same time, it is possible to obtain a remarkable effect of being able to grasp whether the same resident repeatedly uses the facility (the increase in the social participation index is larger than the increase in the number of social participants). This concludes the explanation of data analysis (1). Data Analysis (2) Next, as data analysis (2), the creation of individual aggregate information, which is one of the social participation analysis data, that is, data analysis by participant, will be described. Figure 22 is a flowchart showing the processing of data analysis (2). This flowchart is executed for each participant, that is, for each PID.

[0182] First, in step S201, the data analysis unit 16 sets the PID, period, and UID of the target facility. First, the number of measurements (N) of the UID is set to 0 as an initial setting. These may be specified by the administrative agency terminal 72, or may be set by applying a predetermined rule.

[0183] Next, in step S202, the data analysis unit 16 secures a storage area for storing a personal total information table 188(UT) indicating personal total information in the database 17. Then, in step S203, a predetermined record is read from the behavior history information 175 in the database 17.

[0184] Next, in step S204, the data analysis unit 16 determines whether the behavior type in the read behavior history information (record) is "stay." If it is "stay" (Y), the process proceeds to step S205. If it is not "stay," the process proceeds to step S210.

[0185] Next, in step S205, the data analysis unit 16 judges whether the read behavior history information 175 matches the condition set in step S201. Specifically, it is judged whether it is included in the movement start time and movement end time of the read behavior history information. At this time, it may be judged whether either one is included in the investigation period. It is also judged whether both the PID and UID match. If they match (Y), the process proceeds to step S206. If they do not match (N), the process proceeds to step S210.

[0186] Next, in step S206, the data analysis unit 16 determines whether the target PID is a first-time PID. If the result is that the PID is a first-time PID (Y), the process proceeds to step S208. If the PID is not a first-time PID (N), the process proceeds to step S207.

[0187] Next, in step S207, the data analysis unit 16 updates the total number of visits and the total visit time of each PID for the UID corresponding to the read action history information.

[0188] In step S208, the total number of visits and total visiting time for the corresponding UID and PID are newly generated, and in step S209, the value of N for the corresponding UID is updated.

[0189] Next, in step S210, the data analysis unit 16 determines whether there is any unread behavior history information 175 (records). As a result, if there is (Y), the process proceeds to step S211. If there is not (N), the process proceeds to step S212.

[0190] Next, in step S211, the data analysis unit 16 updates the current target BID. To this end, the data analysis unit 16 identifies, for example, a BID that identifies the next behavior from among the read behavior history information. Then, the process returns to step S203.

[0191] Furthermore, in step S212, the data analysis unit 16 creates the total number of visits and total duration of stay for the relevant UID by accumulating the number of visits and duration of stay.

[0192] Next, in step S213, it is determined whether there are other target UIDs. As a result, if there are other UIDs (Y), the process proceeds to step S214. If there are no other UIDs (N), the process ends. When the process ends, the data analysis unit 16 can cause the created individual summary information to be displayed on the administrative agency terminal 72 via the output unit 12. In step S214, the data analysis unit 16 updates the target UID, and the process proceeds to step S202.

[0193] FIG. 23 shows the individual tally information created by the process in FIG. 22 in the form of individual tally information table 188 (UT). The individual tally information includes the relevant UID, tally start time, tally end time, total number of visits to the relevant PID, total duration of stay, N of the UID, PID of the visited facility, total number of visits to the PID, and total duration of stay. This data analysis (2) makes it possible to grasp the utilization status of each participant at the facility, that is, the status of social participation behavior for each participant. This concludes the explanation of data analysis (2). Data Analysis (3) Next, as data analysis (3), the creation of facility-specific aggregate information, which is one of the social participation analysis data, that is, data analysis for each facility, will be described. Fig. 24 is a flowchart showing the processing of data analysis (3).

[0194] First, in step S301, the data analysis unit 16 sets the PID, period, and UID of the target facility. First, the number of measurements (N) of the UID is set to 0 as an initial setting. These may be specified by the administrative agency terminal 72, or may be set by applying a predetermined rule.

[0195] Next, in step S302, the data analysis unit 16 secures a storage area for storing a facility-specific tally information table 187 (PT) indicating facility-specific tally information in the database 17. Then, in step S303, the data analysis unit 16 sets the UID of the target facility.

[0196] Next, in step S304, a predetermined record is read from the behavior history information 175 in the database 17. Then, in step S305, the data analysis unit 16 determines whether the behavior type in the read behavior history information (record) is a stay. If it is a stay (Y), the process proceeds to step S306. If it is not a stay, the process proceeds to step S311.

[0197] Next, in step S306, the data analysis unit 16 judges whether the read behavior history information 175 matches the condition set in step S301. Specifically, it is judged whether it is included in the movement start time and movement end time of the read behavior history information. At this time, it may be judged whether either one is included in the investigation period. It is also judged whether both the PID and UID match. If they match (Y), the process proceeds to step S307. If they do not match (N), the process proceeds to step S311.

[0198] Next, in step S307, the data analysis unit 16 determines whether the target UID set in step S303 is the first one. If it is the first PID (Y), the process proceeds to step S309. If it is not the first PID (N), the process proceeds to step S308.

[0199] Next, in step S308, the data analysis unit 16 updates the total number of visits and the total visiting time of each PID in the corresponding UID in the read action history information.

[0200] In step S309, the total number of visits and total visit time for the corresponding UID and PID are newly generated, and in step S310, the value of N for the corresponding PID is updated.

[0201] Next, in step S311, the data analysis unit 16 determines whether there is any unread behavior history information 175 (records). As a result, if there is (Y), the process proceeds to step S312. If there is not (N), the process proceeds to step S313.

[0202] Next, in step S312, the data analysis unit 16 updates the current target BID. To this end, the data analysis unit 16 identifies, for example, a BID that identifies the next behavior from among the read behavior history information. Then, the process returns to step S304.

[0203] Furthermore, in step S313, the data analysis unit 16 creates the total number of visits and total duration of stay for the corresponding PID by accumulating the number of visits and duration of stay.

[0204] Next, in step S314, it is determined whether there are other target UIDs. As a result, if there are other UIDs (Y), the process proceeds to step S315. If there are no other UIDs (N), the process ends. When the process ends, the data analysis unit 16 can cause the created individual summary information to be displayed on the administrative agency terminal 72 via the output unit 12. In step S315, the data analysis unit 16 updates the target UID, and the process proceeds to step S303.

[0205] The facility-specific tally information created by the process in Fig. 24 is shown in Fig. 25 in the form of a facility-specific tally information table 187 (PT). The facility-specific tally information includes the target PID, tally start time, tally end time, total number of visits at the target facility, total duration of stay, PID N, UID visited by the visitor, total number of visits at the UID, and total duration of stay. This concludes the explanation of data analysis (3).

[0206] Next, a modified example of data analysis in this embodiment will be described. In the analysis of social participation behavior, it is important to know what social participation category each participant is performing. Therefore, in this modified example, the total number of visits to facilities by social participation category is compiled for social participation behavior. The result is shown in FIG. 39. FIG. 39 is a diagram showing a usage frequency management table 186 in this embodiment. This usage frequency management table 186 is created from a collection of records for each social participation behavior. More specifically, the usage frequency management table 186 has items for each record, such as a counting start time, a counting end time, and a total number of visits by social participation category. Here, the total number of visits by social participation category has items such as work, hobbies (cultural), hobbies (sports), shopping (groceries), shopping (other), library, and others.

[0207] The creation of the usage frequency management table 186 will be described below. First, the data analysis unit 16 reads out the tally start time and tally end time from the person-specific tally information table 188, and records them in the usage frequency management table 186. The data analysis unit 16 also identifies the corresponding registration time in the behavior history information 175 using the recorded tally start time and tally end time as keys. That is, the data analysis unit 16 identifies a record in the behavior history information 175 that corresponds to the tally start time and tally end time. Next, the data analysis unit 16 identifies a social participation category that corresponds to the facility category of the identified record. Then, the data analysis unit 16 counts the identified social participation category and records it in the item of the total number of visits by social participation category.

[0208] As a result, the usage frequency management table 186 shown in FIG. 39 is created. In FIG. 39, the first record (2020.12.01 / 00:00:00:00 to 2020.12.31 / 23:59:59:99) is before participation in the service for performing social participation behavior, and the number of visits indicates 0. The data analysis unit 16 and the incentive value calculation unit 15 can execute information processing for various services using the usage frequency management table 186 created in this way. For example, the incentive value calculation unit 15 can realize point allocation according to the participation frequency by social participation category, such as granting additional points when there is a record of visiting a facility in a social participation category in the following month when there was no visit record in the previous month.

[0209] This concludes the explanation of this embodiment. The discrimination unit 13, index calculation unit 14, incentive value calculation unit 15 and data analysis unit 16 will use the output unit 12 to display on a terminal device or the like.

[0210] The present invention is not limited to the present embodiment, and can be realized in various forms. For example, the behavior analysis device 10 may be provided with a display unit and realized as a so-called standalone device. In addition, advice regarding specific social participation behavior may be output according to data analysis. [Explanation of symbols]

[0211] 1...analysis service center, 10...behavioral analysis device, 11...input section, 12...output section, 13...discrimination section, 14...index calculation section, 15...incentive value calculation section, 16...data analysis section, 17...database, 18-1, 18-2...operation management terminal, 2-1...fitness club, 2-2...store, 2-3...home, 20-1, 20-2, 20-3...mobile terminal, 21...detection device 21, 22...counter terminal, 30...fitness club system, 40...insurance company system, 50...care facility management company system, 60...point management company system, 70-1, 70-2...government agency system, 71-1, 71-2...government agency server, 72-1, 72-2...government agency terminal, 80...network, 90...intranet

Claims

1. In the social participation behavior analysis device that analyzes the social participation behavior of participants, An input unit that receives location information indicating a movement history of each of a plurality of participants; a discrimination unit that uses the location information to create behavior history information indicating behavior histories of the plurality of participants, and discriminates social participation categories of the plurality of participants based on the location information; an index calculation unit that calculates a social participation index indicating a state of involvement with society included in social participation information indicating social participation behavior of each of the plurality of participants identified based on the social participation category; A social participation behavior analysis device having an incentive value calculation unit that calculates, in accordance with the social participation index, an incentive value indicating an incentive for a social participation behavior provider that provides a place for the social participation behavior indicated by a facility included in the behavior history information, and for related parties involved in the social participation behavior, including the multiple participants.

2. 2. The social participation behavior analysis device according to claim 1, The incentive value calculation unit is a social participation behavior analysis device that calculates, as the incentive value, an amount of benefit to be paid to the social participation behavior provider and a number of points to be paid to the participant.

3. 3. The social participation behavior analysis device according to claim 2, The incentive value calculation unit calculates a benefit standard based on the number of visitors to a place provided by the social participation behavior provider and the weight of the social participation behavior in the place, as the benefit amount, and calculates a benefit standard amount by multiplying the benefit standard by the benefit unit price.

4. 4. The social participation behavior analysis device according to claim 3, The incentive value calculation unit is a social participation behavior analysis device that calculates a total benefit amount by adding an additional benefit amount to the benefit base amount when the participant newly participates in social participation behavior in the venue.

5. 3. The social participation behavior analysis device according to claim 2, The incentive value calculation unit calculates a standard point based on the number of visitors to the venue by the participant and the weight of the participant's social participation behavior in the venue, and calculates the standard point number by multiplying the standard point by a point unit price.

6. 6. The social participation behavior analysis device according to claim 5, The incentive value calculation unit is a social participation behavior analysis device that calculates, when the participant newly participates in social participation behavior in the venue, a total number of points by adding an additional number of points to the reference number of points as the number of points.

7. A social participation behavior analysis method for analyzing a participant's social participation behavior using a social participation behavior analysis device, comprising: An input unit receives location information indicating a movement history of each of the plurality of participants; A discrimination unit uses the location information to create behavior history information indicating a behavior history of the plurality of participants, and discriminates social participation categories of the plurality of participants based on the location information; an index calculation unit calculates a social participation index indicating a social involvement state of each of the plurality of participants identified based on the social participation category, the social participation index being included in social participation information indicating the social participation behavior of each of the plurality of participants; A social participation behavior analysis method in which an incentive value calculation unit calculates, according to the social participation index, an incentive value indicating an incentive for a social participation behavior provider who provides a place for the social participation behavior indicated by a facility included in the behavior history information, and for related parties involved in the social participation behavior, including the multiple participants.

8. The social participation behavior analysis method according to claim 7, The social participation behavior analysis method, wherein the incentive value calculation unit calculates, as the incentive value, an amount of benefit to be paid to the social participation behavior provider and a number of points to be paid to the participant.

9. The social participation behavior analysis method according to claim 8, A social participation behavior analysis method in which the incentive value calculation unit calculates a benefit standard based on the number of visitors to a place provided by the social participation behavior provider and the weight of the social participation behavior in that place as the benefit amount, and calculates a benefit standard amount by multiplying the benefit standard by the benefit unit price.

10. The social participation behavior analysis method according to claim 9, A social participation behavior analysis method in which the incentive value calculation unit calculates a total benefit amount by adding an additional benefit amount to the benefit base amount when the participant newly participates in social participation behavior in the venue.

11. The social participation behavior analysis method according to claim 8, The social participation behavior analysis method, in which the incentive value calculation unit calculates a standard point based on the number of visitors to the venue by the participant and the weight of the participant's social participation behavior in the venue, and calculates the standard point number by multiplying the standard point by a point unit price.

12. The social participation behavior analysis method according to claim 11, A social participation behavior analysis method in which the incentive value calculation unit calculates, when the participant newly participates in social participation behavior in the venue, a total number of points by adding an additional number of points to the standard number of points as the number of points.

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