WO2023199522A1 - Action support control device, method, and program - Google Patents

Action support control device, method, and program Download PDF

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Publication number
WO2023199522A1
WO2023199522A1 PCT/JP2022/017948 JP2022017948W WO2023199522A1 WO 2023199522 A1 WO2023199522 A1 WO 2023199522A1 JP 2022017948 W JP2022017948 W JP 2022017948W WO 2023199522 A1 WO2023199522 A1 WO 2023199522A1
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WIPO (PCT)
Prior art keywords
user
job
reward
work
processing unit
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PCT/JP2022/017948
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French (fr)
Japanese (ja)
Inventor
諭 高津
朋子 柴田
寛 吉田
昌史 坂本
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日本電信電話株式会社
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Priority to PCT/JP2022/017948 priority Critical patent/WO2023199522A1/en
Publication of WO2023199522A1 publication Critical patent/WO2023199522A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management

Definitions

  • One aspect of the present invention relates to a behavior support control device, method, and program used, for example, to support human behavior.
  • the point incentive system is well known as a mechanism to encourage people's behavior.
  • the point incentive system aims to improve the motivation and retention rate of employees by giving rewards such as salaries in the form of points, thereby revitalizing corporate organizations.
  • the following technologies have been proposed.
  • Patent Document 1 describes a method of calculating distances between exhibits using position information of terminals and determining incentive points according to the calculated distances.
  • Patent Document 2 discloses that a person's health risk is calculated from the person's behavioral history, and the risk is presented to the person's relatives and friends so that the person's relatives and friends give advice to the person. , describes a system in which incentive points are given to relatives and friends in proportion to the reduction in the risk of the person mentioned above as a result of their advice.
  • This invention was made in view of the above circumstances, and aims to provide a technology that makes it possible to improve work efficiency while suppressing the total cost of remuneration.
  • one aspect of the behavior support control device or the behavior support control method according to the present invention is to provide a behavior support control device or a behavior support control method according to the present invention.
  • the expected psychological cost of the user corresponding to the conditions related to the unfinished work is calculated, and the calculated expected psychological cost of each user is compared with a predetermined objective variable related to the unfinished work. determining the user who is capable of handling the completed work, and adjusting the reward points for the user who is capable of handling the uncompleted work so that the reward points are minimized according to the expected psychological cost; This is what I did.
  • each user's expected psychological cost is determined for an uncompleted task according to its remuneration conditions, and by comparing each user's expected psychological cost and the remuneration condition for the task, the A user who can handle the unfinished business is determined, and reward points are set for the user.
  • users who can perform a task and their remuneration are determined according to the user's psychological cost regarding the relationship between the task and the reward, so it is possible to have the appropriate user perform each task with the appropriate reward. It becomes possible.
  • FIG. 1 is a diagram showing a schematic configuration of a behavior support system including a behavior support control device according to an embodiment of the present invention.
  • FIG. 2 is a block diagram showing an example of the hardware configuration of the behavior support control device according to an embodiment of the present invention.
  • FIG. 3 is a block diagram showing an example of the software configuration of the behavior support control device according to an embodiment of the present invention.
  • FIG. 4 is a flowchart showing an example of the processing procedure and processing contents of the basic information acquisition processing executed by the control unit of the behavior support control device shown in FIG.
  • FIG. 5 is a flowchart illustrating an example of processing procedures and processing contents of various determination processes based on basic information, which are executed by the control unit of the behavior support control device shown in FIG. FIG.
  • FIG. 6 is a flowchart illustrating an example of the procedure and contents of a point setting process executed by the control unit of the behavior support control device shown in FIG. 3 when there is only one user who can handle a job.
  • FIG. 7 is a flowchart illustrating an example of the processing procedure and contents of the point setting process and user selection process when there are multiple users who can handle a job, which are executed by the control unit of the behavior support control device shown in FIG. 3. be.
  • FIG. 8 is a flowchart illustrating an example of the processing procedure and processing contents of point setting processing and user selection processing when there is no user available for the job, which is executed by the control unit of the behavior support control device shown in FIG. 3. .
  • FIG. 7 is a flowchart illustrating an example of the processing procedure and contents of the point setting process and user selection process when there are multiple users who can handle a job, which are executed by the control unit of the behavior support control device shown in FIG. 3. be.
  • FIG. 8 is a flowchart illustrating an example of the
  • FIG. 9 is a diagram showing an example of job information acquired by the basic information acquisition process shown in FIG. 4.
  • FIG. 10 is a diagram showing an example of user information acquired by the basic information acquisition process shown in FIG. 4.
  • FIG. 11 is a diagram showing an example of area information acquired by the basic information acquisition process shown in FIG. 4.
  • FIG. 12 is a diagram showing an example of remuneration information acquired by the basic information acquisition process shown in FIG. 4.
  • FIG. 13 is a diagram showing an example of condition-based list data for each job generated by the basic information organizing process shown in FIG. 5.
  • FIG. 14 is a diagram showing an example in which the condition-specific list data shown in FIG. 13 is digitized.
  • FIG. 15 is a diagram showing condition-by-condition list data used to explain an example of the reward vector formula formulation process shown in FIG.
  • FIG. 16 is a diagram showing condition-by-condition list data used to explain an example of the process of determining a user who can handle a job and the process of determining a job whose completion deadline is approaching, shown in FIG. 5.
  • FIG. 17 is a diagram for explaining an example of the point setting process when there is only one user who can handle the job shown in FIG. 6.
  • FIG. 18 is a diagram for explaining an example of the point setting process and user selection process when there are multiple users who can handle the job shown in FIG. 7.
  • FIG. 19 is a diagram for explaining an example of the point setting process and the user selection process shown in FIG. 8 when there is no user available for the job.
  • a case will be described in which, for example, a package delivery company supports the actions of a plurality of delivery workers regarding delivery operations by using an incentive point system.
  • the delivery person will hereinafter be referred to as a user
  • the delivery job will be referred to as a job.
  • the type and content of work is not limited to field work such as delivery work, but there are various other possible examples, such as cases in which employees perform office work, design work, or production work at home or any other location. .
  • FIG. 1 is a diagram showing a schematic configuration of a behavior support system including a behavior support control device according to an embodiment of the present invention.
  • the behavior support system includes a behavior support control device SV, and between this behavior support control device SV and user terminals UT1 to UTn used by a plurality of users A to N engaged in work, respectively, This enables information communication via the network NW.
  • the user terminals UT1 to UTn are used by users to execute jobs, and are composed of, for example, smartphones. Note that wearable terminals, tablet terminals, personal computers, and the like may be used as the user terminals UT1 to UTn.
  • the network NW includes, for example, a wide area network centered on the Internet, and an access network for accessing this wide area network.
  • the access network for example, a wired or wireless public communication network, a wired or wireless LAN (Local Area Network), or a CATV (Cable Television) network is used.
  • the network NW may be configured only by a local area network such as a LAN or a wireless LAN.
  • Behavior support control device SV 2 and 3 are block diagrams showing examples of the hardware and software configurations of the behavior support control device SV, respectively.
  • the behavior support control device SV is operated by a delivery company, for example, and consists of a server computer installed on the web or in the cloud.
  • the behavior support control device SV includes a control unit 1 using a hardware processor such as a central processing unit (CPU), and a memory having a program storage unit 2 and a data storage unit 3.
  • the unit and a communication interface (hereinafter referred to as I/F) section 4 are connected via a bus 5.
  • the communication I/F section 4 performs information communication with the user terminals UT1 to UTn under the control of the control section 1 using a communication protocol defined by the network NW.
  • the program storage unit 2 is configured by combining, for example, a non-volatile memory such as an SSD (Solid State Drive) that can be written to and read from at any time as a storage medium, and a non-volatile memory such as a ROM (Read Only Memory).
  • a non-volatile memory such as an SSD (Solid State Drive) that can be written to and read from at any time as a storage medium
  • a non-volatile memory such as a ROM (Read Only Memory).
  • middleware such as an OS (Operating System)
  • application programs necessary for executing various control processes according to one embodiment are stored. Note that hereinafter, the OS and each application program will be collectively referred to as a program.
  • the data storage unit 3 is, for example, a combination of a nonvolatile memory such as an SSD that can be written to and read from at any time as a storage medium, and a volatile memory such as a RAM (Random Access Memory), and is an embodiment of the present invention.
  • the system includes a job information storage unit 31, a user information storage unit 32, an area information storage unit 33, a remuneration information storage unit 34, and a condition list data storage unit 35. ing.
  • the job information storage unit 31 stores various information regarding each job as job information.
  • the job information includes, for example, location information of the delivery destination, area information, distance from the base, completion deadline, delivery history, and the like.
  • the delivery history includes, for example, the person in charge and the date and time of completion.
  • the user information storage unit 32 stores information regarding each user who is a delivery person as user information.
  • the user information includes information representing the current location of each user, but may also include skills, achievements, average remuneration, etc. for each user.
  • the area information storage unit 33 stores information regarding each target area of the delivery service as area information.
  • the area information includes, for example, the population density of the area, the number of slopes existing in the area, and current weather conditions such as temperature and humidity.
  • the remuneration information storage unit 34 includes, for example, the amount of results corresponding to one point, the amount, the type of remuneration other than the amount, etc. As the amount of results, for example, the distance traveled is used.
  • the condition-by-condition list data storage unit 35 stores condition-by-condition list data in which elements (variables) related to each job are categorized into psychological cost and reward conditions.
  • the condition-specific list data is created by the control unit 1, which will be described later, based on the job information, user information, area information, and remuneration information.
  • the target is field work such as home delivery work
  • the above job information, user information, area information, and remuneration information are acquired and list data by condition is generated, but indoor work such as document creation is targeted.
  • Area information does not necessarily need to be used when targeting.
  • the control unit 1 includes a job information acquisition processing unit 11, a user information acquisition processing unit 12, an area information acquisition processing unit 13, and a remuneration information acquisition processing unit as processing functions used to implement an embodiment of the present invention. 14, a cost/reward condition arrangement processing section 15, and a completed job extraction processing section 21, a psychological cost judgment/determination processing section 22, a reward vector determination processing section 23, and a cost/reward judgment processing section 24. , a job completion status determination processing section 25 , a point correction processing section 26 , a user selection processing section 27 , and an output processing section 28 .
  • processing units 11 to 15 and 21 to 28 are all realized by causing the hardware processor of the control unit 1 to execute an application program stored in the program storage unit 2.
  • processing units 11 to 15 and 21 to 28 may be realized using hardware such as LSI (Large Scale Integration) or ASIC (Application Specific Integrated Circuit).
  • Job information represents attributes related to a job, and is generated each time a new job is requested, for example, in a business management device (not shown) of a delivery company, and the contents are updated according to the progress of the job. .
  • the job information acquisition processing unit 11 acquires the job information from the business management device via the communication I/F unit 4, and stores the acquired job information in the job information storage unit 31.
  • User information represents attributes related to users, and is generated for each user in a business management device of a delivery company, for example, and is further updated according to the user's response to a job.
  • the user information acquisition processing unit 12 acquires the user information from the business management device via the communication I/F unit 4, and stores the acquired user information in the user information storage unit 32.
  • Area information which represents attributes related to an area, is generated for each area with a preset range, for example, in the business management device of a delivery company, and is further chronologically generated according to weather information obtained from a weather information site. will be updated.
  • the area information acquisition processing unit 13 acquires the area information from the business management device via the communication I/F unit 4, and stores the acquired area information in the area information storage unit 33.
  • the remuneration information represents attributes related to remuneration, is created by the administrator in the business management device, and is updated by the administrator, for example, at regular intervals.
  • the remuneration information acquisition processing unit 14 acquires the remuneration information from the business management device via the communication I/F unit 4, and stores the acquired remuneration information in the remuneration information storage unit 34.
  • the cost/remuneration condition arrangement processing unit 15 organizes a plurality of elements (variables) related to the job for each job into psychological cost-related conditions and remuneration-related conditions to generate list data, and organizes the plurality of elements (variables) related to the job for each job to generate list data, and The list data is stored in the condition-specific list data storage section 35.
  • the completed job extraction processing unit 21 extracts completed jobs processed by the same user under the same conditions based on the condition-specific list data stored in the condition-specific list data storage unit 35. .
  • the psychological cost judgment/determination processing section 22 uses the condition-specific list data stored in the condition-specific list data storage section 35 to determine the results when dealing with each user under the same job conditions for previously completed jobs. Calculate the psychological cost and determine its maximum value. Then, the psychological cost judgment/determination processing unit 22 uses a value corresponding to the amount of results per point (for example, distance from the base) as a reference variable, and defines a linear vector expression representing this reference variable. Alternatively, a linear vector equation is defined in which the amount of results per point is used as the objective variable of multiple regression analysis, for example.
  • the reward vector determination processing unit 23 groups jobs for each user. Then, an analysis (for example, multiple regression analysis) using the maximum value of the reference variable among the completed jobs for each group as the objective variable is performed using the above linear vector formula, and this is used to determine the psychology of each user under the same job conditions. Generate a reward vector formula to find the target cost. That is, the reward vector determination processing unit 23 formulates the degree of behavior according to the reward condition for each user.
  • an analysis for example, multiple regression analysis
  • the cost/reward determination processing unit 24 calculates the expected psychological cost for each user by substituting the job conditions of the uncompleted job as an explanatory variable into the above-mentioned remuneration vector formula. Then, by comparing the calculated assumed psychological cost of each user with the target variable of the unfinished job, a user who can handle the unfinished job is determined.
  • the job completion status determination processing unit 25 calculates the remaining time until the completion deadline of the uncompleted job based on the list data stored in the condition-specific list data storage unit 35, and calculates the remaining time until the completion deadline of the uncompleted job, based on the calculated remaining time. Then, it is determined whether the uncompleted job is a job whose completion deadline is approaching, that is, an emergency response job.
  • the point correction processing unit 26 combines the determination result of the user who can handle the uncompleted job obtained by the cost/reward determination processing unit 24 and the determination result of the emergency response job obtained by the job completion status determination processing unit 25. , a process is performed to modify the points of the user's reward vector for the job for each combination pattern.
  • the user selection processing unit 27 selects the optimal user to execute the incomplete job for each of the combination patterns.
  • the output processing unit 28 outputs the assumed psychological cost and remuneration conditions for the uncompleted job calculated by the cost/reward determination processing unit 24, and the corrections made by each user to the uncompleted job calculated by the point correction processing unit 26. Generate action support information including subsequent points. Then, the generated action support information is transmitted from the communication I/F unit 4 to the user terminals UT1 to UTn used by the corresponding users.
  • FIG. 4 is a flowchart showing an example of the processing procedure and processing contents of the basic information acquisition process executed by the control unit 1 of the behavior support control device SV.
  • the control unit 1 of the behavior support control device SV receives the job information via the communication I/F unit 4 in step S10 under the control of the job information acquisition processing unit 11, and stores the received job information in job information storage.
  • the information is stored in the section 31.
  • FIG. 9 shows an example of job information.
  • the job information is linked to the job ID for each job J1, J2, etc. corresponding to the delivery destination, and includes the area ID of the job, the user ID of the person handling the job, the completion date and time, and the information from the base. It stores multiple job-related elements such as distance, required skills, and completion deadline.
  • job-related elements are not limited to the above-mentioned elements, and may include, for example, the type and weight of the delivery item, and can be set arbitrarily.
  • user information is generated for each of the users A, B, .
  • the user information is transmitted from the business management device to the behavior support control device SV every time it is generated or updated.
  • the control unit 1 of the behavior support control device SV receives the user information via the communication I/F unit 4 in step S11 under the control of the user information acquisition processing unit 12, and converts the received user information into user information. It is stored in the storage unit 32.
  • FIG. 10 shows an example of user information.
  • the user information is linked to the user ID of each user A, B, etc., and includes multiple elements related to the user, such as the latitude and longitude indicating the current location, address, number of complaints from customers, etc. It has been memorized.
  • the elements related to user information are not limited to the above example, and may include age, gender, years of experience, performance value, etc., and can be set arbitrarily.
  • area information is generated for each predefined area, and this area information is updated according to changes in weather conditions, for example.
  • the area information is transmitted from the business management device to the behavior support control device SV every time it is generated or updated.
  • the control unit 1 of the behavior support control device SV receives the area information via the communication I/F unit 4 in step S12 under the control of the area information acquisition processing unit 13, and converts the received area information into area information. It is stored in the storage unit 33.
  • FIG. 11 shows an example of area information.
  • the area information includes, for example, each area Ea, Eb, etc., linked to its area ID, and includes multiple elements related to the area such as date, weather, temperature, humidity, number of slopes, etc. It's something I remember.
  • the elements related to area information are not limited to the above example, and may include area, slope slope, length, etc., and can be set arbitrarily.
  • remuneration information is managed at fixed time intervals such as daily, weekly, monthly, etc.
  • the remuneration information is transmitted from the business management device to the behavior support control device SV every time it is changed.
  • the control unit 1 of the behavior support control device SV receives the remuneration information via the communication I/F unit 4 in step S13 under the control of the remuneration information acquisition processing unit 14, and converts the received remuneration information into remuneration information.
  • the information is stored in the storage unit 34.
  • FIG. 12 shows an example of remuneration information.
  • the remuneration information defines a plurality of elements related to remuneration, such as the amount of results per point, monetary remuneration, appreciation remuneration, etc., and these elements are updated monthly.
  • the amount of results for example, the distance traveled is used.
  • FIG. 5 is a flowchart showing an example of processing procedures and processing contents of various judgment processes based on basic information.
  • step S21 generation of job-related list data by condition
  • the control unit 1 of the behavior support control device SV under the control of the cost/reward condition arrangement processing unit 15,
  • step S21 elements related to each job are organized into conditions related to psychological costs and conditions related to rewards, thereby generating job condition list data.
  • FIG. 13 shows an example of organized job list data by condition.
  • the job ID is associated with multiple elements included in the conditions related to psychological cost and multiple elements included in the conditions related to remuneration. It shows.
  • Information related to psychological costs includes, for example, responders, area ID, completion date and time, completion deadline, distance from base, weather conditions including weather, temperature, humidity, wind force, etc., number of slopes, and number of complaints from customers. is included.
  • the conditions related to the reward include, for example, the amount of results per point, the monetary amount, and the gratitude reward.
  • the cost/reward condition arrangement processing unit 15 digitizes each element of the above-mentioned condition-based list data other than the elements expressed by numerical values.
  • the weather is the amount of precipitation
  • the area ID is the population density
  • the gratitude reward is a binary value of "1” indicating "Yes/No”. , "0” respectively.
  • the above condition list data includes necessary skills, social contribution (SDGs), etc. as one of the conditions, these can be changed to “1” or “0” to indicate “Yes/No”. Replace.
  • the cost/reward condition arrangement processing unit 15 updates and stores the latest condition-specific list data in the condition-specific list data storage unit 35 each time the condition-specific list data of the job is newly generated or updated.
  • control unit 1 of the behavior support control device SV extracts the conditions stored in the condition-specific list data storage unit 35 in step S22. Search separate list data and extract jobs completed in the past.
  • step S23 the control section 1 of the behavior support control device SV first performs the following according to the above conditions in step S23. Based on the condition-specific list data stored in the list data storage unit 35, the psychological cost that can be handled under the same job conditions for each user is calculated, and the maximum value thereof is determined.
  • step S24 the psychological cost judgment/determination processing unit 22 sets a value corresponding to the amount of results per point (for example, distance from the base) as a reference variable based on the above-mentioned condition-specific list data, and sets this criterion as a reference variable.
  • a value corresponding to the amount of results per point for example, distance from the base
  • this criterion as a reference variable.
  • a linear vector expression to represent the variable.
  • a linear vector equation is defined in which the amount of results per point is used as the objective variable of multiple regression analysis, for example.
  • the linear vector equation in this case is, for example, Objective variable (distance from base) is defined as: a population density + b precipitation + c temperature + d number of slopes + ... + e points. Note that the completion deadline and completion date and time are not taken into consideration at this point.
  • the control unit 1 of the behavior support control device SV then groups jobs for each user in step S25 under the control of the reward vector determination processing unit 23. Then, for each group, a multiple regression analysis using the maximum value of the reference variables as the objective variable among the completed jobs extracted by the completed job extraction processing unit 21 is performed using the linear vector equation. Then, the vector formula for determining the psychological cost under the same job conditions for each user, obtained through this analysis, is taken as the reward vector formula representing the degree of behavior according to the user's reward condition.
  • d1, d2, . . . indicate weighting coefficients for each job condition as an explanatory variable.
  • step S26 Determining whether there is a user who can handle the uncompleted job
  • the control unit 1 of the behavior support control device SV first calculates the above reward vector formula in step S26. By substituting the job conditions of uncompleted jobs as explanatory variables, the expected psychological cost for each user is calculated. Then, in step S27, the cost/reward determination processing unit 24 compares the calculated assumed psychological cost of each user with the objective variable of the unfinished job, thereby identifying users who can handle the unfinished job. Determine the presence or absence.
  • step S28 under the control of the job completion status determination processing unit 25, the control unit 1 of the behavior support control device SV selects the condition-by-condition list data storage unit 35.
  • the remaining time until the completion deadline of the unfinished job is calculated based on the condition-specific list data stored in Determine whether the job requires emergency response.
  • the remaining time until the completion deadline can be determined as the difference between the completion deadline and the current time.
  • the control unit 1 of the behavior support control device SV performs each judgment obtained by the cost/reward judgment processing unit 24 and the job completion status judgment processing unit 25. Combine patterns. Then, under the control of the user selection processing unit 27 and the point correction processing unit 26, for each of the above combination patterns, the user to be associated with the uncompleted job is selected and the user is made more likely to take action regarding the uncompleted job. Perform point correction processing for this purpose.
  • the point correction processing section 26 uses, for example, the following calculation formula. (Bpt ⁇ Cpt/Dpt) ⁇ Xa ⁇ Ya ⁇ Za...(1)
  • Bpt is the standard point (e.g. 1pt)
  • Cpt is the psychological cost (e.g. 300m)
  • Dpt is the amount of results per point (e.g. 10m)
  • Xa is the attractiveness improvement coefficient (e.g. 2x)
  • Ya is an attractiveness reduction coefficient (for example, 0.5 times)
  • Za is a reward adjustment coefficient (for example, 1.5 times).
  • the remuneration adjustment coefficient Za is a coefficient that ensures the minimum attractiveness of the job to the user.
  • FIG. 6 is a flowchart showing an example of the processing procedure and processing contents of the point correction processing and user selection processing executed by the point correction processing section 26 and the user selection processing section 27 when the combination patterns are A+D and B+E. Further, FIG. 17 is a diagram for explaining an example of the processing.
  • the point correction processing unit 26 determines whether the combination pattern is A+D or A+E in steps S30 and S32.
  • the reward vectors IB3 and IC3 of users B and C for unfinished job J3 are short by IB3 LAK and IC3 LAK with respect to the objective variables of unfinished job J3, whereas the reward vectors of user A are Vector IA3 is higher than the objective variable of incomplete job J3. Therefore, in this case, the only user who can handle the unfinished job J3 is A.
  • the point correction processing unit 26 determines that it is [pattern A+D] and proceeds to step S31. In this step S31, the point correction processing unit 26 passes the reward points of user A for the incomplete job J3 to the output processing unit 28 as is without correction.
  • the point correction processing unit 26 determines [pattern A+E], and in step S33, out of the plurality of jobs J1, J2, and J3 that the user can handle, the attractiveness level of the emergency response job J3 is compared with that of other jobs J1. , J2, the points of the reward vector IA3 for user A's emergency response job J3 are increased using the above equation (1).
  • the points of the reward vector IA3 for the emergency response job J3 are the highest.
  • the points of the reward vector IA3 for the emergency response job J3 are multiplied by the attractiveness improvement coefficient Xa, thereby modifying the points so that the points of the reward vector IA3 for the emergency response job J3 become, for example, 31 points or more.
  • step S34 the point correction processing unit 26 passes the corrected points for user A who can handle the emergency response job J3 to the output processing unit 28.
  • FIG. 7 is a flowchart showing an example of the processing procedure and processing contents of the point correction processing and user selection processing executed by the point correction processing section 26 and the user selection processing section 27 when the combination patterns are B+D and B+E. Further, FIG. 18 is a diagram for explaining an example of the processing.
  • the point correction processing unit 26 determines whether the above combination pattern is B+D or B+E in steps S40 and S44. For example, as shown in FIG. 18, it is assumed that there are three users A, B, and C who can handle the incomplete job J3, and the incomplete job J3 is not an emergency job. In this case, first, in step S41, the user selection processing unit 27 selects a user who can respond to job J3 with the lowest points. In the example shown in FIG. 18, user A has the smallest support points for job J3, so the user selection processing unit 27 selects user A.
  • step S42 the point correction processing unit 26 changes the points of the reward vectors IB3 and IC3 for the job J3 of the users B and C, who were not selected in the step S41, to the points of the reward vectors IB3 and IC3 for the user A, who were not selected in the step S41, in order to reduce the attractiveness of the job J3.
  • the points of reward vector IA3 for job J3 are decreased to be lower than the points of reward vector IA3 for job J3.
  • the point correction processing unit 26 adjusts the points of reward vectors IB3 and IC3 for job J3 of users B and C to be less than or equal to the points (10pt) of reward vector IA3 for job J3 of user A. Then, the points of the current reward vectors IB3 and IC3 for the job J3 of users B and C are multiplied by attractiveness reduction coefficients Yb and Yc, and the values are reduced.
  • the point correction processing unit 26 passes the corrected points for each of the users A, B, and C to the output processing unit 28 in step S43.
  • step S45 the point correction processing unit 26 determines that for each of users A, B, and C, if there are multiple jobs that the user can handle, the point for emergency response job J3 is the highest among them.
  • the points of the reward vectors IA3, IB3, and IC3 for the emergency response job J3 of users A, B, and C are multiplied by attractiveness improvement coefficients Xa, Xb, and Xc, respectively, so that the points are corrected.
  • step S46 the user selection processing unit 27 selects the user who has the smallest points after modification for the emergency response job J3 from among users A, B, and C who can respond to the emergency response job J3. .
  • the user A's post-correction points (20pt ⁇ Xa) for job J3 are the smallest, so the user selection processing unit 27 selects the user A.
  • step S47 the point correction processing unit 26 changes the points of the reward vectors IB3 and IC3 for the job J3 of the users B and C, who were not selected in the step S46, to the points of the reward vectors IB3 and IC3 of the user A, who were not selected in the step S46, in order to reduce the attractiveness of the job J3.
  • the points of the reward vector IA3 for job J3 are decreased to be smaller than the points of the reward vector IA3 for job J3.
  • the point correction processing unit 26 determines that the points of reward vectors IB3 and IC3 for job J3 of users B and C are less than or equal to the points (20pt ⁇ Xa) of reward vector IA3 for job J3 of user A.
  • the points of the current reward vectors IB3 and IC3 for job J3 of users B and C are multiplied by attractiveness reduction coefficients Yb and Yc, respectively, to reduce their values.
  • the point correction processing unit 26 passes the corrected points to be presented to the users A, B, and C to the output processing unit 28 in step S48.
  • FIG. 8 is a flowchart showing an example of the processing procedure and processing contents of the point correction processing and user selection processing executed by the point correction processing section 26 and the user selection processing section 27 when the combination patterns are C+D and C+E. Further, FIG. 19 is a diagram for explaining an example of the processing.
  • the point correction processing unit 26 determines whether the combination pattern is C+D or C+E. For example, as shown in FIG. 19, it is assumed that there is no user who can handle incomplete jobs J1 and J2.
  • the point correction processing unit 26 determines that the pattern is [pattern C+D] in step S50, and proceeds to step S51. Then, in step S51, the points of the reward vector for the incomplete jobs J1 and J2 are increased for each of the users A, B, and C.
  • reward vectors IA1 and IA2 for uncompleted jobs J1 and J2 of user A are multiplied by reward adjustment coefficients Za1 and Za2 to add reward points IA1 ADJ and IA2 ADJ .
  • reward vectors IB2 and IC2 for uncompleted jobs J2 of users B and C are multiplied by reward adjustment coefficients Zb and Zc, respectively, and reward points IB2 ADJ and IC2 ADJ are added.
  • user A can respond to each of the unfinished jobs J1 and J2, and users A, B, and C can respond to unfinished job J2.
  • the user selection processing unit 27 selects the most suitable user for matching the incomplete jobs J1 and J2.
  • only user A can handle job J1, so user A is selected as is.
  • a plurality of users A, B, and C can handle job J2. Therefore, from among users A, B, and C, user A is selected whose adjusted remuneration vectors IA2+IA2 ADJ , IB2+IB2 ADJ , and IC2+IC2 ADJ for uncompleted job J2 are the lowest.
  • step S53 the point correction processing unit 26 changes the reward vectors IB2+IB2 ADJ and IC2+IC2 ADJ for the job J2 of users B and C not selected in the step S52 to the reward vector IA2+IA2 ADJ for the job J2 of the user A.
  • the reward vectors IB2+IB2 ADJ and IC2+IC2 ADJ are multiplied by attractiveness reduction coefficients Yb and Yc, respectively, to reduce their values so that they become smaller.
  • step S54 the point correction processing section 26 passes the corrected points of each of the users A, B, and C for the incomplete jobs J1 and J2 to the output processing section 28.
  • step S56 the point correction processing unit 26 adjusts the points of the reward vector for each incomplete job J1, J2 for each user A, B, C, as in the case where the job is not an emergency response job. , thereby allowing at least one user to respond to the unfinished jobs J1 and J2.
  • step S57 the point correction processing unit 26 determines that the adjusted reward vector IA2+IA2 ADJ for the emergency response job J2 is the same as that for the job J1 whose deadline is not approaching, for the user A who can respond to the incomplete jobs J1 and J2.
  • the remuneration vector IA2 for the emergency response job J2 is multiplied by the attractiveness improvement coefficient so that the adjusted remuneration vector IA1+IA1 ADJ becomes higher.
  • step S58 the user selection processing unit 27 selects the adjusted remuneration vector for the emergency response job J2 from among the users A, B, and C who can respond to the emergency response job J2. Select the user with the smallest ADJ .
  • the adjusted reward vector IA2+IA2 ADJ (10pt ⁇ Za2) of user A for job J2 is the smallest, so the user selection processing unit 27 selects user A.
  • step S59 the point correction processing unit 26 determines that the adjusted reward vectors IB2+IB2 ADJ , IC2+IC2 ADJ for the job J2 of the users B and C not selected in the step S58 are adjusted for the job J2 of the user A.
  • the reward points are reduced by multiplying the reward vectors IB2+IB2 ADJ and IC2+IC2 ADJ by attractiveness reduction coefficients Yb and Yc, respectively, so that the points are lower than the points of the subsequent reward vector IA2+IA2 ADJ (10pt ⁇ Za2).
  • the point correction processing unit 26 passes the corrected points for each of the incomplete jobs J1 and J2 of the users A, B, and C to the output processing unit 28 in step S60.
  • users A, B, and C receive the behavior support information through their own user terminals UT1, UT2, and UT3, respectively. Users A, B, and C then select an uncompleted job as an action target based on the corrected points included in the received action support information, and execute the job.
  • the maximum psychological cost that each user can deal with under the same conditions is calculated based on the psychological cost and reward conditions related to past completed jobs, and Using the maximum cost value, a reward vector formula is generated to determine the psychological cost under the same job conditions for each user. Then, using the above reward vector formula, calculate the user's expected psychological cost for each combination of user and uncompleted job, and compare this expected psychological cost with the reward to make it possible to deal with the uncompleted job. Determine the user. Based on this determination result, the user who is able to handle the unfinished job and has the lowest reward points is selected, and points are modified to make it easier for the user to select and execute the unfinished job. We are trying to present the points to the above users.
  • the reward points for the emergency response job are Modify the reward points so that they are higher than the reward points for the job. Therefore, when there are multiple jobs that a user can handle, it is possible to increase the probability that the user will select and execute the emergency response job from among the multiple jobs, thereby giving priority to the emergency response job. It becomes possible to execute the
  • a modification is made to increase the reward points of each user for the unfinished job to generate users who can respond to the job. Then, a user with the lowest reward points is selected from among the generated users, and points are corrected so that the user can more easily select and execute the unfinished job. Therefore, it is possible to have the user select and execute an uncompleted job with a high probability of receiving an appropriate reward.
  • points may be corrected by adding or subtracting an attractiveness improvement coefficient Xa, an attractiveness reduction coefficient Ya, or a remuneration adjustment coefficient Za to the amount of results per point.
  • the point correction formula in this case is shown below.
  • Bpt ⁇ Cpt/Dpt (Bpt ⁇ Cpt/Dpt) ⁇ Pa ⁇ Qa ⁇ Ra...(2)
  • Bpt is the standard point (e.g. 1pt)
  • Cpt is the psychological cost (e.g. 300m)
  • Dpt is the amount of results per point (e.g. 10m)
  • Pa is the attractiveness improvement coefficient (e.g. 10pt)
  • Qa is the The attractiveness reduction coefficient (e.g. 10pt)
  • Ra are the reward adjustment coefficients (e.g. 10pt).
  • the remuneration adjustment coefficient Ra is a coefficient that ensures the minimum attractiveness of the job to the user.
  • the above job information, user information, area information, and remuneration information acquisition processing by the control unit 1 of the behavior support control device SV is performed every time information is newly generated in the work management device and each time the information is updated. Although it is preferable that the process be performed at regular intervals, it may be performed at other fixed time intervals or at arbitrary timing.
  • whether or not the target job is an emergency response job is determined based on one threshold value.
  • the degree of urgency of the emergency response job can be further determined.
  • the points may be modified to make them easier to select.
  • the point correction processing unit 26 performs point correction processing based only on the determination result of the user who can handle the job.
  • the present invention is not limited to the above-described embodiments as they are, but can be embodied by modifying the constituent elements at the implementation stage without departing from the spirit of the invention.
  • various inventions can be formed by appropriately combining the plurality of components disclosed in the above embodiments. For example, some components may be deleted from all the components shown in the embodiments. Furthermore, components from different embodiments may be combined as appropriate.
  • Control unit 2 For Program storage unit 3
  • Data storage unit 4 For Communication I/F unit 5... Bus 11
  • Job information acquisition processing unit 12 For User information acquisition processing unit 13
  • Completed job extraction processing section 22 ...Psychological cost judgment/determination processing section 23
  • Reward vector determination processing section 24 ...Cost/reward judgment processing section 25
  • Job completion status judgment processing Units 26...Point correction processing unit 27
  • User selection processing unit 28 for Output processing unit 31
  • Job information storage unit 32 ForUser information storage unit 33
  • Area information storage unit 34 for Reward information storage unit 35...Condition list data storage unit

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Abstract

One aspect of the present invention includes: managing work basic information in which work operations are associated with a plurality of conditions regarding a mental cost and a reward of a user; obtaining, for each user, on the basis of the work basic information, a maximum mental cost according to the conditions regarding a completed work operation, which is of the work operations completed in the past; and generating, on the basis of the maximum mental cost, a reward vector expression representing the relation between the conditions and the mental cost. Then, using the reward vector expression, an expected mental cost of a user corresponding to the conditions regarding an uncompleted work operation is obtained for each user, a user who can handle the uncompleted work operation is determined by comparing the expected mental cost of each user with a predetermined objective variable regarding the uncompleted work operation, and a reward point of the user for the work operation is adjusted such that the user who has the minimum expected mental cost among the users executes the work operation.

Description

行動支援制御装置、方法およびプログラムBehavior support control device, method and program
　この発明の一態様は、例えば人の行動を支援するために用いる行動支援制御装置、方法およびプログラムに関する。 One aspect of the present invention relates to a behavior support control device, method, and program used, for example, to support human behavior.
　人の行動を促す仕組みとして、ポイントインセンティブ制度が良く知られている。ポイントインセンティブ制度は、従業者に給与等の報奨をポイントとして与えることで、従業者のモチベーションや定着率を向上させ、これにより企業組織の活性化を図るもので、インセンティブポイントを決める既存の技術としては、以下のような技術が提案されている。 The point incentive system is well known as a mechanism to encourage people's behavior. The point incentive system aims to improve the motivation and retention rate of employees by giving rewards such as salaries in the form of points, thereby revitalizing corporate organizations. The following technologies have been proposed.
　例えば特許文献１には、展示物と展示物の間の距離を端末の位置情報を用いて算出し、算出した距離に応じたインセンティブポイントを決定する手法が記載されている。 For example, Patent Document 1 describes a method of calculating distances between exhibits using position information of terminals and determining incentive points according to the calculated distances.
　また、例えば特許文献２には、ある人の健康上のリスクをその行動履歴から計算し、上記人の親族や友人に上記リスクを提示することで親族や友人から上記人に対し助言を行わせ、助言の結果上記人のリスクが下がった分だけ親族や友人にインセンティブポイントを与える仕組みが記載されている。 In addition, for example, Patent Document 2 discloses that a person's health risk is calculated from the person's behavioral history, and the risk is presented to the person's relatives and friends so that the person's relatives and friends give advice to the person. , describes a system in which incentive points are given to relatives and friends in proportion to the reduction in the risk of the person mentioned above as a result of their advice.
日本国特開２０１８－２０５８３３号公報Japanese Patent Application Publication No. 2018-205833 日本国特許第６６８７７９５号公報Japanese Patent No. 6687795
　ところが、特許文献１および特許文献２に記載された技術では、単に移動距離や健康リスクに応じてインセンティブポイントを決定するものとなっている。このため、例えば最近増加しているギグワーカーと呼ばれる人たちのように自由な時間帯に働く人たちに対しては、インセンティブポイントを適切に与えることが困難である。 However, in the techniques described in Patent Document 1 and Patent Document 2, incentive points are simply determined according to travel distance and health risk. For this reason, it is difficult to appropriately provide incentive points to people who work during their free time, such as gig workers, who have been increasing recently.
　そこで、このように多様化する働き方をする人たちに対しては、押し並べて高めのインセンティブポイント（報酬）を一律に付与することが一般的となっている。しかし、このようにすると、与える報酬のトータルコストが増大するばかりでなく、報酬が与えられても人によって行動意欲に個人差があるため、全体として期待する業務効率が得られるとは限らない。 Therefore, it is common practice to uniformly allocate higher incentive points (remuneration) to people who work in increasingly diverse ways of working. However, in this case, not only does the total cost of rewards increase, but even if rewards are given, there are individual differences in motivation for action, so it is not always possible to achieve the expected operational efficiency as a whole.
　この発明は上記事情に着目してなされたもので、報酬のトータルコストを抑えつつ、業務効率の向上を可能にする技術を提供しようとするものである。 This invention was made in view of the above circumstances, and aims to provide a technology that makes it possible to improve work efficiency while suppressing the total cost of remuneration.
　上記課題を解決するためにこの発明に係る行動支援制御装置または行動支援制御方法の一態様は、業務に対するユーザの行動を報酬ポイントを用いて支援する際に、前記業務に対し、前記ユーザの心理的コストおよび報酬に係る複数の条件を関連付けた業務基礎情報を管理し、前記業務基礎情報に基づいて、前記ユーザごとに、前記業務のうち過去に完了した完了業務に係る前記条件に応じた最大心理的コストを求め、前記最大心理的コストをもとに前記条件と前記心理的コストとの関係を表す報酬ベクトル式を生成し、前記ユーザごとに、前記報酬ベクトル式を用いて、前記業務のうち未完了業務に係る前記条件に対応する前記ユーザの予想心理的コストを求め、求めた各ユーザの前記予想心理的コストを前記未完了業務に係る所定の目的変数と比較することにより、前記未完了業務に対応可能な前記ユーザを判定し、前記未完了業務に対応可能な前記ユーザに対し、前記予想心理的コストに応じて前記報酬ポイントが最小となるように前記報酬ポイントを調整するようにしたものである。 In order to solve the above problems, one aspect of the behavior support control device or the behavior support control method according to the present invention is to provide a behavior support control device or a behavior support control method according to the present invention. management of business basic information that associates multiple conditions related to costs and remuneration, and based on the business basic information, for each user, the maximum A psychological cost is determined, a reward vector formula representing the relationship between the conditions and the psychological cost is generated based on the maximum psychological cost, and the reward vector formula is used to determine the performance of the task for each user. Of these, the expected psychological cost of the user corresponding to the conditions related to the unfinished work is calculated, and the calculated expected psychological cost of each user is compared with a predetermined objective variable related to the unfinished work. determining the user who is capable of handling the completed work, and adjusting the reward points for the user who is capable of handling the uncompleted work so that the reward points are minimized according to the expected psychological cost; This is what I did.
　この発明の一態様によれば、未完了業務に対しその報酬条件に応じた各ユーザの予想心理的コストが求められ、各ユーザの予想心理的コストと業務に対する報酬条件とを比較することにより上記未完了業務に対応可能なユーザが判定され、当該ユーザに対する報酬ポイントが設定される。すなわち、業務と報酬との関係に対するユーザの心理的コストに応じて、業務に対応可能なユーザとその報酬が決定されるので、各業務を適切なユーザに適切な報酬で実行してもらうことが可能となる。 According to one aspect of the present invention, each user's expected psychological cost is determined for an uncompleted task according to its remuneration conditions, and by comparing each user's expected psychological cost and the remuneration condition for the task, the A user who can handle the unfinished business is determined, and reward points are set for the user. In other words, users who can perform a task and their remuneration are determined according to the user's psychological cost regarding the relationship between the task and the reward, so it is possible to have the appropriate user perform each task with the appropriate reward. It becomes possible.
　すなわちこの発明の一態様によれば、報酬のトータルコストを抑えつつ、業務効率の向上を可能にする技術を提供することができる。 That is, according to one aspect of the present invention, it is possible to provide a technology that enables improvement of work efficiency while suppressing the total cost of remuneration.
図１は、この発明の一実施形態に係る行動支援制御装置を備える行動支援システムの概略構成を示す図である。FIG. 1 is a diagram showing a schematic configuration of a behavior support system including a behavior support control device according to an embodiment of the present invention. 図２は、この発明の一実施形態に係る行動支援制御装置のハードウェア構成の一例を示すブロック図である。FIG. 2 is a block diagram showing an example of the hardware configuration of the behavior support control device according to an embodiment of the present invention. 図３は、この発明の一実施形態に係る行動支援制御装置のソフトウェア構成の一例を示すブロック図である。FIG. 3 is a block diagram showing an example of the software configuration of the behavior support control device according to an embodiment of the present invention. 図４は、図３に示す行動支援制御装置の制御部が実行する基礎情報取得処理の処理手順と処理内容の一例を示すフローチャートである。FIG. 4 is a flowchart showing an example of the processing procedure and processing contents of the basic information acquisition processing executed by the control unit of the behavior support control device shown in FIG. 図５は、図３に示す行動支援制御装置の制御部が実行する、基礎情報に基づく各種判定処理の処理手順と処理内容の一例を示すフローチャートである。FIG. 5 is a flowchart illustrating an example of processing procedures and processing contents of various determination processes based on basic information, which are executed by the control unit of the behavior support control device shown in FIG. 図６は、図３に示す行動支援制御装置の制御部が実行する、ジョブに対応可能なユーザが１人の場合のポイント設定処理の処理手順と処理内容の一例を示すフローチャートである。FIG. 6 is a flowchart illustrating an example of the procedure and contents of a point setting process executed by the control unit of the behavior support control device shown in FIG. 3 when there is only one user who can handle a job. 図７は、図３に示す行動支援制御装置の制御部が実行する、ジョブに対応可能なユーザが複数人の場合のポイント設定処理およびユーザ選択処理の処理手順と処理内容の一例を示すフローチャートである。FIG. 7 is a flowchart illustrating an example of the processing procedure and contents of the point setting process and user selection process when there are multiple users who can handle a job, which are executed by the control unit of the behavior support control device shown in FIG. 3. be. 図８は、図３に示す行動支援制御装置の制御部が実行する、ジョブに対応可能なユーザが存在しない場合のポイント設定処理およびユーザ選択処理の処理手順と処理内容の一例を示すフローチャートである。FIG. 8 is a flowchart illustrating an example of the processing procedure and processing contents of point setting processing and user selection processing when there is no user available for the job, which is executed by the control unit of the behavior support control device shown in FIG. 3. . 図９は、図４に示す基礎情報取得処理により取得されるジョブ情報の一例を示す図である。FIG. 9 is a diagram showing an example of job information acquired by the basic information acquisition process shown in FIG. 4. 図１０は、図４に示す基礎情報取得処理により取得されるユーザ情報の一例を示す図である。FIG. 10 is a diagram showing an example of user information acquired by the basic information acquisition process shown in FIG. 4. 図１１は、図４に示す基礎情報取得処理により取得されるエリア情報の一例を示す図である。FIG. 11 is a diagram showing an example of area information acquired by the basic information acquisition process shown in FIG. 4. 図１２は、図４に示す基礎情報取得処理により取得される報酬情報の一例を示す図である。FIG. 12 is a diagram showing an example of remuneration information acquired by the basic information acquisition process shown in FIG. 4. 図１３は、図５に示す基礎情報整理処理により生成される各ジョブの条件別一覧データの一例を示す図である。FIG. 13 is a diagram showing an example of condition-based list data for each job generated by the basic information organizing process shown in FIG. 5. 図１４は、図１３に示す条件別一覧データを数値化した例を示す図である。FIG. 14 is a diagram showing an example in which the condition-specific list data shown in FIG. 13 is digitized. 図１５は、図５に示す、報酬ベクトル式の定式化処理の一例を説明するために用いる条件別一覧データを示す図である。FIG. 15 is a diagram showing condition-by-condition list data used to explain an example of the reward vector formula formulation process shown in FIG. 図１６は、図５に示す、ジョブに対応可能なユーザの判定処理および完了期限が迫ったジョブの判定処理の一例を説明するために用いる条件別一覧データを示す図である。FIG. 16 is a diagram showing condition-by-condition list data used to explain an example of the process of determining a user who can handle a job and the process of determining a job whose completion deadline is approaching, shown in FIG. 5. 図１７は、図６に示す、ジョブに対応可能なユーザが１人の場合のポイント設定処理の一例を説明するための図である。FIG. 17 is a diagram for explaining an example of the point setting process when there is only one user who can handle the job shown in FIG. 6. 図１８は、図７に示す、ジョブに対応可能なユーザが複数人の場合のポイント設定処理およびユーザ選択処理の一例を説明するための図である。FIG. 18 is a diagram for explaining an example of the point setting process and user selection process when there are multiple users who can handle the job shown in FIG. 7. 図１９は、図８に示す、ジョブに対応可能なユーザが存在しない場合のポイント設定処理およびユーザ選択処理の一例を説明するための図である。FIG. 19 is a diagram for explaining an example of the point setting process and the user selection process shown in FIG. 8 when there is no user available for the job.
　以下、図面を参照してこの発明に係わる実施形態を説明する。 Hereinafter, embodiments of the present invention will be described with reference to the drawings.
　［一実施形態］
　この発明の一実施形態では、例えば荷物の宅配事業者が、複数の配達員の配達業務に係る行動を、インセンティブポイント制度を利用して支援する場合を例にとって説明する。この例では、以後配達員をユーザと呼び、また配達業務をジョブと呼ぶ。 [One embodiment]
In one embodiment of the present invention, a case will be described in which, for example, a package delivery company supports the actions of a plurality of delivery workers regarding delivery operations by using an incentive point system. In this example, the delivery person will hereinafter be referred to as a user, and the delivery job will be referred to as a job.
　なお、業務の種類や内容については、宅配業のようなフィールド業務に限らず、従業者が自宅や任意の場所で事務処理業務や設計業務、生産業務を行う場合等、種々の例が考えられる。 The type and content of work is not limited to field work such as delivery work, but there are various other possible examples, such as cases in which employees perform office work, design work, or production work at home or any other location. .
　（構成例）
　（１）システム
　図１は、この発明の一実施形態に係る行動支援制御装置を備える行動支援システムの概略構成を示す図である。 (Configuration example)
(1) System FIG. 1 is a diagram showing a schematic configuration of a behavior support system including a behavior support control device according to an embodiment of the present invention.
　一実施形態に係る行動支援システムは、行動支援制御装置ＳＶを備え、この行動支援制御装置ＳＶと、業務に従事する複数のユーザＡ～Ｎがそれぞれ使用するユーザ端末ＵＴ１～ＵＴｎとの間で、ネットワークＮＷを介して情報通信を可能にしたものである。 The behavior support system according to one embodiment includes a behavior support control device SV, and between this behavior support control device SV and user terminals UT1 to UTn used by a plurality of users A to N engaged in work, respectively, This enables information communication via the network NW.
　ユーザ端末ＵＴ１～ＵＴｎは、ユーザがジョブを実行するために使用するもので、例えばスマートフォンにより構成される。なお、ユーザ端末ＵＴ１～ＵＴｎとしては、他にウェアラブル端末やタブレット型端末、パーソナルコンピュータ等が用いられてもよい。 The user terminals UT1 to UTn are used by users to execute jobs, and are composed of, for example, smartphones. Note that wearable terminals, tablet terminals, personal computers, and the like may be used as the user terminals UT1 to UTn.
　ネットワークＮＷは、例えばインターネットを中核とする広域ネットワークと、この広域ネットワークにアクセスするためのアクセスネットワークとを備える。アクセスネットワークとしては、例えば、有線または無線を使用する公衆通信ネットワーク、有線または無線を使用するＬＡＮ（Local Area Network）、ＣＡＴＶ（Cable Television）ネットワークが使用される。なお、行動支援システムが例えば企業内または事業所構内で運用される場合、ネットワークＮＷは例えばＬＡＮまたは無線ＬＡＮ等の構内ネットワークのみにより構成されてもよい。 The network NW includes, for example, a wide area network centered on the Internet, and an access network for accessing this wide area network. As the access network, for example, a wired or wireless public communication network, a wired or wireless LAN (Local Area Network), or a CATV (Cable Television) network is used. Note that, when the behavior support system is operated within a company or office premises, for example, the network NW may be configured only by a local area network such as a LAN or a wireless LAN.
　（２）行動支援制御装置ＳＶ
　図２および図３は、それぞれ行動支援制御装置ＳＶのハードウェアおよびソフトウェアの構成の一例を示すブロック図である。 (2) Behavior support control device SV
2 and 3 are block diagrams showing examples of the hardware and software configurations of the behavior support control device SV, respectively.
　行動支援制御装置ＳＶは、例えば宅配事業者が運用するもので、ウェブ上またはクラウド上に設置されるサーバコンピュータからなる。行動支援制御装置ＳＶは、中央処理ユニット（Central Processing Unit：ＣＰＵ）等のハードウェアプロセッサを使用した制御部１を備え、この制御部１に対し、プログラム記憶部２およびデータ記憶部３を有する記憶ユニットと、通信インタフェース（以後インタフェースをＩ／Ｆと称する）部４を、バス５を介して接続したものとなっている。 The behavior support control device SV is operated by a delivery company, for example, and consists of a server computer installed on the web or in the cloud. The behavior support control device SV includes a control unit 1 using a hardware processor such as a central processing unit (CPU), and a memory having a program storage unit 2 and a data storage unit 3. The unit and a communication interface (hereinafter referred to as I/F) section 4 are connected via a bus 5.
　通信Ｉ／Ｆ部４は、制御部１の制御の下、ネットワークＮＷにより定義される通信プロトコルを使用して、ユーザ端末ＵＴ１～ＵＴｎとの間で情報通信を行う。 The communication I/F section 4 performs information communication with the user terminals UT1 to UTn under the control of the control section 1 using a communication protocol defined by the network NW.
　プログラム記憶部２は、例えば、記憶媒体としてＳＳＤ（Solid State Drive）等の随時書込みおよび読出しが可能な不揮発性メモリと、ＲＯＭ（Read Only Memory）等の不揮発性メモリとを組み合わせて構成したもので、ＯＳ（Operating System）等のミドルウェアに加えて、一実施形態に係る各種制御処理を実行するために必要なアプリケーション・プログラムを格納する。なお、以後ＯＳと各アプリケーション・プログラムとをまとめてプログラムと称する。 The program storage unit 2 is configured by combining, for example, a non-volatile memory such as an SSD (Solid State Drive) that can be written to and read from at any time as a storage medium, and a non-volatile memory such as a ROM (Read Only Memory). In addition to middleware such as an OS (Operating System), application programs necessary for executing various control processes according to one embodiment are stored. Note that hereinafter, the OS and each application program will be collectively referred to as a program.
　データ記憶部３は、例えば、記憶媒体として、ＳＳＤ等の随時書込みおよび読出しが可能な不揮発性メモリと、ＲＡＭ（Random Access Memory）等の揮発性メモリと組み合わせたもので、この発明の一実施形態を実施するために必要な主たる記憶部として、ジョブ情報記憶部３１と、ユーザ情報記憶部３２と、エリア情報記憶部３３と、報酬情報記憶部３４と、条件別一覧データ記憶部３５とを備えている。 The data storage unit 3 is, for example, a combination of a nonvolatile memory such as an SSD that can be written to and read from at any time as a storage medium, and a volatile memory such as a RAM (Random Access Memory), and is an embodiment of the present invention. As main storage units necessary for implementing the above, the system includes a job information storage unit 31, a user information storage unit 32, an area information storage unit 33, a remuneration information storage unit 34, and a condition list data storage unit 35. ing.
　ジョブ情報記憶部３１は、各ジョブに関する種々情報をジョブ情報として記憶する。ジョブ情報は、例えば配達先の位置情報、エリア情報、拠点からの距離、完了期限、配達履歴等を含む。配達履歴には、例えば対応者および完了日時が含まれる。 The job information storage unit 31 stores various information regarding each job as job information. The job information includes, for example, location information of the delivery destination, area information, distance from the base, completion deadline, delivery history, and the like. The delivery history includes, for example, the person in charge and the date and time of completion.
　ユーザ情報記憶部３２は、配達員である各ユーザに関する情報をユーザ情報として記憶する。ユーザ情報には、ユーザごとにその現在地を表す情報が含まれるが、業務に対するスキルや実績、報酬の平均値などが含まれていてもよい。 The user information storage unit 32 stores information regarding each user who is a delivery person as user information. The user information includes information representing the current location of each user, but may also include skills, achievements, average remuneration, etc. for each user.
　エリア情報記憶部３３は、宅配サービスの各対象エリアに関する情報をエリア情報として記憶する。エリア情報は、例えばエリアの人口密度、エリア内に存在する坂の数、現在の天候や温度、湿度等の気象条件等を含む。 The area information storage unit 33 stores information regarding each target area of the delivery service as area information. The area information includes, for example, the population density of the area, the number of slopes existing in the area, and current weather conditions such as temperature and humidity.
　報酬情報記憶部３４は、例えば１ポイントに対応する成果量、金額、金額以外の報酬の種類等を含む。成果量としては、例えば移動距離が用いられる。 The remuneration information storage unit 34 includes, for example, the amount of results corresponding to one point, the amount, the type of remuneration other than the amount, etc. As the amount of results, for example, the distance traveled is used.
　条件別一覧データ記憶部３５は、各ジョブに関わる要素（変数）を心理的コストおよび報酬の各条件に分けて整理した条件別一覧データを記憶する。条件別一覧データは、後述する制御部１により、上記ジョブ情報、ユーザ情報、エリア情報および報酬情報をもとに作成される。 The condition-by-condition list data storage unit 35 stores condition-by-condition list data in which elements (variables) related to each job are categorized into psychological cost and reward conditions. The condition-specific list data is created by the control unit 1, which will be described later, based on the job information, user information, area information, and remuneration information.
　なお、この例では宅配業務等のフィールド業務を対象としているため、上記ジョブ情報、ユーザ情報、エリア情報および報酬情報を取得し、条件別一覧データを生成しているが、書類作成などの屋内業務を対象とする場合には、エリア情報は必ずしも用いなくてもよい。 In this example, since the target is field work such as home delivery work, the above job information, user information, area information, and remuneration information are acquired and list data by condition is generated, but indoor work such as document creation is targeted. Area information does not necessarily need to be used when targeting.
　制御部１は、この発明の一実施形態を実施するために用いる処理機能として、ジョブ情報取得処理部１１と、ユーザ情報取得処理部１２と、エリア情報取得処理部１３と、報酬情報取得処理部１４と、コスト／報酬条件整理処理部１５とを備え、さらに完了ジョブ抽出処理部２１と、心理的コスト判定／決定処理部２２と、報酬ベクトル決定処理部２３と、コスト／報酬判定処理部２４と、ジョブ完了状況判定処理部２５と、ポイント修正処理部２６と、ユーザ選択処理部２７と、出力処理部２８とを備える。 The control unit 1 includes a job information acquisition processing unit 11, a user information acquisition processing unit 12, an area information acquisition processing unit 13, and a remuneration information acquisition processing unit as processing functions used to implement an embodiment of the present invention. 14, a cost/reward condition arrangement processing section 15, and a completed job extraction processing section 21, a psychological cost judgment/determination processing section 22, a reward vector determination processing section 23, and a cost/reward judgment processing section 24. , a job completion status determination processing section 25 , a point correction processing section 26 , a user selection processing section 27 , and an output processing section 28 .
　これらの処理部１１～１５、２１～２８は、何れもプログラム記憶部２に格納されたアプリケーション・プログラムを制御部１のハードウェアプロセッサに実行させることにより実現される。 These processing units 11 to 15 and 21 to 28 are all realized by causing the hardware processor of the control unit 1 to execute an application program stored in the program storage unit 2.
　なお、上記処理部１１～１５、２１～２８の一部または全部は、ＬＳＩ（Large Scale Integration）やＡＳＩＣ（Application Specific Integrated Circuit）等のハードウェアを用いて実現されてもよい。 Note that some or all of the processing units 11 to 15 and 21 to 28 may be realized using hardware such as LSI (Large Scale Integration) or ASIC (Application Specific Integrated Circuit).
　ジョブ情報は、ジョブに係る属性を表すもので、例えば宅配事業者の業務管理装置（図示省略）において、新規ジョブが依頼されるごとに生成され、さらにジョブの進捗に応じて内容が更新される。ジョブ情報取得処理部１１は、上記ジョブ情報を上記業務管理装置から通信Ｉ／Ｆ部４を介して取得し、取得した上記ジョブ情報をジョブ情報記憶部３１に記憶する。 Job information represents attributes related to a job, and is generated each time a new job is requested, for example, in a business management device (not shown) of a delivery company, and the contents are updated according to the progress of the job. . The job information acquisition processing unit 11 acquires the job information from the business management device via the communication I/F unit 4, and stores the acquired job information in the job information storage unit 31.
　ユーザ情報は、ユーザに係る属性を表すもので、例えば宅配事業者の業務管理装置において、ユーザごとに生成され、さらにジョブに対するユーザの対応状況に応じて更新される。ユーザ情報取得処理部１２は、上記ユーザ情報を上記業務管理装置から通信Ｉ／Ｆ部４を介して取得し、取得した上記ユーザ情報をユーザ情報記憶部３２に記憶する。 User information represents attributes related to users, and is generated for each user in a business management device of a delivery company, for example, and is further updated according to the user's response to a job. The user information acquisition processing unit 12 acquires the user information from the business management device via the communication I/F unit 4, and stores the acquired user information in the user information storage unit 32.
　エリア情報、エリアに係る属性を表すもので、例えば宅配事業者の業務管理装置において、予め範囲が設定されたエリアごとに生成され、さらに例えば気象情報サイトから取得される気象情報に応じて時系列で更新される。エリア情報取得処理部１３は、上記エリア情報を上記業務管理装置から通信Ｉ／Ｆ部４を介して取得し、取得した上記エリア情報をエリア情報記憶部３３に記憶する。 Area information, which represents attributes related to an area, is generated for each area with a preset range, for example, in the business management device of a delivery company, and is further chronologically generated according to weather information obtained from a weather information site. will be updated. The area information acquisition processing unit 13 acquires the area information from the business management device via the communication I/F unit 4, and stores the acquired area information in the area information storage unit 33.
　報酬情報は、報酬に係る属性を表すもので、上記業務管理装置において管理者により作成され、かつ例えば一定期間ごとに管理者により更新される。報酬情報取得処理部１４は、上記報酬情報を上記業務管理装置から通信Ｉ／Ｆ部４を介して取得し、取得した上記報酬情報を報酬情報記憶部３４に記憶する。 The remuneration information represents attributes related to remuneration, is created by the administrator in the business management device, and is updated by the administrator, for example, at regular intervals. The remuneration information acquisition processing unit 14 acquires the remuneration information from the business management device via the communication I/F unit 4, and stores the acquired remuneration information in the remuneration information storage unit 34.
　コスト／報酬条件整理処理部１５は、ジョブごとに当該ジョブに関する複数の要素（変数）を心理的コストに係る条件および報酬に係る条件ごとに整理して一覧データを生成し、生成した上記条件別の一覧データを条件別一覧データ記憶部３５に記憶する。 The cost/remuneration condition arrangement processing unit 15 organizes a plurality of elements (variables) related to the job for each job into psychological cost-related conditions and remuneration-related conditions to generate list data, and organizes the plurality of elements (variables) related to the job for each job to generate list data, and The list data is stored in the condition-specific list data storage section 35.
　完了ジョブ抽出処理部２１は、上記条件別一覧データ記憶部３５に記憶された条件別一覧データをもとに、完了済のジョブを同一の条件で同一のユーザにより処理されたものごとに抽出する。 The completed job extraction processing unit 21 extracts completed jobs processed by the same user under the same conditions based on the condition-specific list data stored in the condition-specific list data storage unit 35. .
　心理的コスト判定／決定処理部２２は、上記条件別一覧データ記憶部３５に記憶された条件別一覧データをもとに、過去に完了したジョブについてユーザごとに同一のジョブ条件で対応したときの心理的コストを算出し、その最大値を決定する。そして、心理的コスト判定／決定処理部２２は、ポイント当たりの成果量に相当する値（例えば拠点からの距離）を基準変数とし、この基準変数を表す線形ベクトル式を定義する。或いは、上記ポイント当たりの成果量を例えば重回帰分析の目的変数とする線形ベクトル式を定義する。 The psychological cost judgment/determination processing section 22 uses the condition-specific list data stored in the condition-specific list data storage section 35 to determine the results when dealing with each user under the same job conditions for previously completed jobs. Calculate the psychological cost and determine its maximum value. Then, the psychological cost judgment/determination processing unit 22 uses a value corresponding to the amount of results per point (for example, distance from the base) as a reference variable, and defines a linear vector expression representing this reference variable. Alternatively, a linear vector equation is defined in which the amount of results per point is used as the objective variable of multiple regression analysis, for example.
　報酬ベクトル決定処理部２３は、ユーザごとにジョブをグループ化する。そして、このグループごとに完了済のジョブのうち基準変数の最大値を目的変数とする分析（例えば重回帰分析）を上記線形ベクトル式を用いて行い、これによりユーザごとの同一のジョブ条件における心理的コストを求める報酬ベクトル式を生成する。すなわち、報酬ベクトル決定処理部２３は、ユーザごとに報酬条件に応じた行動度合いを定式化する。 The reward vector determination processing unit 23 groups jobs for each user. Then, an analysis (for example, multiple regression analysis) using the maximum value of the reference variable among the completed jobs for each group as the objective variable is performed using the above linear vector formula, and this is used to determine the psychology of each user under the same job conditions. Generate a reward vector formula to find the target cost. That is, the reward vector determination processing unit 23 formulates the degree of behavior according to the reward condition for each user.
　コスト／報酬判定処理部２４は、上記報酬ベクトル式に、未完了ジョブのジョブ条件を説明変数として代入することにより、ユーザごとの想定される心理的コストを算出する。そして、算出した上記各ユーザの想定心理的コストを上記未完了ジョブの目的変数とそれぞれ比較することにより、上記未完了ジョブに対応可能なユーザを判定する。 The cost/reward determination processing unit 24 calculates the expected psychological cost for each user by substituting the job conditions of the uncompleted job as an explanatory variable into the above-mentioned remuneration vector formula. Then, by comparing the calculated assumed psychological cost of each user with the target variable of the unfinished job, a user who can handle the unfinished job is determined.
　ジョブ完了状況判定処理部２５は、上記条件別一覧データ記憶部３５に記憶された一覧データをもとに、未完了ジョブの完了期限までの残り時間を算出し、算出した上記残り時間をもとに上記未完了ジョブが完了期限の迫っているジョブ、つまり緊急対応ジョブであるか否か判定する。 The job completion status determination processing unit 25 calculates the remaining time until the completion deadline of the uncompleted job based on the list data stored in the condition-specific list data storage unit 35, and calculates the remaining time until the completion deadline of the uncompleted job, based on the calculated remaining time. Then, it is determined whether the uncompleted job is a job whose completion deadline is approaching, that is, an emergency response job.
　ポイント修正処理部２６は、上記コスト／報酬判定処理部２４により得られる未完了ジョブに対応可能ユーザの判定結果と、上記ジョブ完了状況判定処理部２５により得られる緊急対応ジョブの判定結果とを組合せ、その組合せパターンごとにジョブに対するユーザの報酬ベクトルのポイントを修正する処理を行う。 The point correction processing unit 26 combines the determination result of the user who can handle the uncompleted job obtained by the cost/reward determination processing unit 24 and the determination result of the emergency response job obtained by the job completion status determination processing unit 25. , a process is performed to modify the points of the user's reward vector for the job for each combination pattern.
　ユーザ選択処理部２７は、上記組合せパターンごとに、上記未完了ジョブを実行させる上で最適なユーザを選択する。 The user selection processing unit 27 selects the optimal user to execute the incomplete job for each of the combination patterns.
　出力処理部２８は、上記コスト／報酬判定処理部２４により算出された未完了ジョブに対する想定心理的コストおよび報酬条件と、上記ポイント修正処理部２６により算出された、未完了ジョブに対する各ユーザの修正後ポイントとを含む行動支援情報を生成する。そして、生成した上記行動支援情報を、通信Ｉ／Ｆ部４から対応するユーザが使用するユーザ端末ＵＴ１～ＵＴｎへ送信する。 The output processing unit 28 outputs the assumed psychological cost and remuneration conditions for the uncompleted job calculated by the cost/reward determination processing unit 24, and the corrections made by each user to the uncompleted job calculated by the point correction processing unit 26. Generate action support information including subsequent points. Then, the generated action support information is transmitted from the communication I/F unit 4 to the user terminals UT1 to UTn used by the corresponding users.
　（動作例）
　次に、以上のように構成された行動支援制御装置ＳＶの動作例を説明する。 (Operation example)
Next, an example of the operation of the behavior support control device SV configured as above will be explained.
　（１）基礎情報の取得
　図４は、行動支援制御装置ＳＶの制御部１が実行する基礎情報取得処理の処理手順と処理内容の一例を示すフローチャートである。 (1) Acquisition of basic information FIG. 4 is a flowchart showing an example of the processing procedure and processing contents of the basic information acquisition process executed by the control unit 1 of the behavior support control device SV.
　（１－１）ジョブ情報の取得
　宅配事業者が運用する業務管理装置において、ジョブ情報が生成または更新されると、生成または更新された上記ジョブ情報が業務管理装置から行動支援制御装置ＳＶに向け送信される。 (1-1) Acquisition of job information When job information is generated or updated in the business management device operated by the delivery company, the generated or updated job information is sent from the business management device to the behavior support control device SV. Sent.
　行動支援制御装置ＳＶの制御部１は、ジョブ情報取得処理部１１の制御の下、ステップＳ１０において上記ジョブ情報を通信Ｉ／Ｆ部４を介して受信し、受信した上記ジョブ情報をジョブ情報記憶部３１に記憶する。 The control unit 1 of the behavior support control device SV receives the job information via the communication I/F unit 4 in step S10 under the control of the job information acquisition processing unit 11, and stores the received job information in job information storage. The information is stored in the section 31.
　図９は、ジョブ情報の一例を示すものである。同図に示すようにジョブ情報は、例えば配達先に対応するジョブＪ１，Ｊ２，…ごとに、ジョブＩＤに紐付けて、当該ジョブのエリアＩＤ、対応者のユーザＩＤ、完了日時、拠点からの距離、必要スキル、完了期限等の、ジョブに係る複数の要素を記憶したものとなっている。なお、ジョブに係る要素としては、上記各要素に限定されるものではなく、例えば配達物の種類や重量などが含まれていてもよく、任意に設定可能である。 FIG. 9 shows an example of job information. As shown in the figure, the job information is linked to the job ID for each job J1, J2, etc. corresponding to the delivery destination, and includes the area ID of the job, the user ID of the person handling the job, the completion date and time, and the information from the base. It stores multiple job-related elements such as distance, required skills, and completion deadline. Note that job-related elements are not limited to the above-mentioned elements, and may include, for example, the type and weight of the delivery item, and can be set arbitrarily.
　（１－２）ユーザ情報の取得
　業務管理装置では、配達員であるユーザＡ，Ｂ，…の各々についてユーザ情報が生成され、さらにこのユーザ情報はユーザの行動に応じて更新される。そして、ユーザ情報は、生成または更新されるごとに業務管理装置から行動支援制御装置ＳＶへ送信される。 (1-2) Acquisition of user information In the business management device, user information is generated for each of the users A, B, . The user information is transmitted from the business management device to the behavior support control device SV every time it is generated or updated.
　行動支援制御装置ＳＶの制御部１は、ユーザ情報取得処理部１２の制御の下、ステップＳ１１において、上記ユーザ情報を通信Ｉ／Ｆ部４を介して受信し、受信した上記ユーザ情報をユーザ情報記憶部３２に記憶する。 The control unit 1 of the behavior support control device SV receives the user information via the communication I/F unit 4 in step S11 under the control of the user information acquisition processing unit 12, and converts the received user information into user information. It is stored in the storage unit 32.
　図１０は、ユーザ情報の一例を示すものである。同図に示すようにユーザ情報は、例えばユーザＡ，Ｂ，…ごとに、そのユーザＩＤに紐付けて、現在位置を示す緯度経度や住所、顧客からのクレーム数等のユーザに係る複数の要素を記憶したものとなっている。なお、ユーザ情報に係る要素は上記例に限るものではなく、年齢、性別、経験年数、実績値等が含まれていてもよく、任意に設定可能である。 FIG. 10 shows an example of user information. As shown in the figure, the user information is linked to the user ID of each user A, B, etc., and includes multiple elements related to the user, such as the latitude and longitude indicating the current location, address, number of complaints from customers, etc. It has been memorized. Note that the elements related to user information are not limited to the above example, and may include age, gender, years of experience, performance value, etc., and can be set arbitrarily.
　（１－３）エリア情報の取得
　業務管理装置では、予め区分設定されたエリアごとにエリア情報が生成され、このエリア情報は例えば気象条件の変化に応じて更新される。そして、エリア情報は、生成または更新されるごとに業務管理装置から行動支援制御装置ＳＶへ送信される。 (1-3) Acquisition of area information In the business management device, area information is generated for each predefined area, and this area information is updated according to changes in weather conditions, for example. The area information is transmitted from the business management device to the behavior support control device SV every time it is generated or updated.
　行動支援制御装置ＳＶの制御部１は、エリア情報取得処理部１３の制御の下、ステップＳ１２において、上記エリア情報を通信Ｉ／Ｆ部４を介して受信し、受信した上記エリア情報をエリア情報記憶部３３に記憶する。 The control unit 1 of the behavior support control device SV receives the area information via the communication I/F unit 4 in step S12 under the control of the area information acquisition processing unit 13, and converts the received area information into area information. It is stored in the storage unit 33.
　図１１は、エリア情報の一例を示すものである。同図に示すようにエリア情報は、例えばエリアＥａ，Ｅｂ，…ごとに、そのエリアＩＤに紐付けて、年月日、天候、気温、湿度、坂の数等のエリアに係る複数の要素を記憶したものとなっている。なお、エリア情報に係る要素は上記例に限るものではなく、面積、坂の勾配や長さ等が含まれていても良く、任意に設定可能である。 FIG. 11 shows an example of area information. As shown in the figure, the area information includes, for example, each area Ea, Eb, etc., linked to its area ID, and includes multiple elements related to the area such as date, weather, temperature, humidity, number of slopes, etc. It's something I remember. Note that the elements related to area information are not limited to the above example, and may include area, slope slope, length, etc., and can be set arbitrarily.
　（１－４）報酬情報の取得
　業務管理装置では、報酬情報が例えば日、週、月等の一定の時間間隔で管理される。そして、上記報酬情報は変更されるごとに業務管理装置から行動支援制御装置ＳＶへ送信される。 (1-4) Acquisition of remuneration information In the business management device, remuneration information is managed at fixed time intervals such as daily, weekly, monthly, etc. The remuneration information is transmitted from the business management device to the behavior support control device SV every time it is changed.
　行動支援制御装置ＳＶの制御部１は、報酬情報取得処理部１４の制御の下、ステップＳ１３において、上記報酬情報を通信Ｉ／Ｆ部４を介して受信し、受信した上記報酬情報を報酬情報記憶部３４に記憶する。 The control unit 1 of the behavior support control device SV receives the remuneration information via the communication I/F unit 4 in step S13 under the control of the remuneration information acquisition processing unit 14, and converts the received remuneration information into remuneration information. The information is stored in the storage unit 34.
　図１２は、報酬情報の一例を示すものである。同図に示すように報酬情報は、例えば１ポイント当たりの成果量、金銭報酬、感謝報酬など、報酬に係る複数の要素を定義したもので、これらの要素は月ごとに更新される。成果量としては、例えば移動距離が用いられる。 FIG. 12 shows an example of remuneration information. As shown in the figure, the remuneration information defines a plurality of elements related to remuneration, such as the amount of results per point, monetary remuneration, appreciation remuneration, etc., and these elements are updated monthly. As the amount of results, for example, the distance traveled is used.
　（２）基礎情報に基づく各種判定
　図５は、基礎情報に基づく各種判定処理の処理手順と処理内容の一例を示すフローチャートである。 (2) Various Judgments Based on Basic Information FIG. 5 is a flowchart showing an example of processing procedures and processing contents of various judgment processes based on basic information.
　（２－１）ジョブに係る条件別一覧データの生成
　行動支援制御装置ＳＶの制御部１は、上記基礎情報の少なくとも１つが更新されると、コスト／報酬条件整理処理部１５の制御の下、先ずステップＳ２１において、ジョブごとに当該ジョブに係る要素を心理的コストに係る条件と報酬に係る条件のそれぞれに整理し、これによりジョブの条件別一覧データを生成する。 (2-1) Generation of job-related list data by condition When at least one of the above basic information is updated, the control unit 1 of the behavior support control device SV, under the control of the cost/reward condition arrangement processing unit 15, First, in step S21, elements related to each job are organized into conditions related to psychological costs and conditions related to rewards, thereby generating job condition list data.
　図１３は、整理されたジョブの条件別一覧データの一例を示すものである。この例では、ジョブＪ１，Ｊ２，…ごとに、そのジョブＩＤに対し、心理的コストに係る条件に含まれる複数の要素と、報酬に係る条件に含まれる複数の要素とを対応付けたものを示している。心理的コストに係る情報には、例えば、対応者、エリアＩＤ、完了日時、完了期限、拠点からの距離、天候や温度、湿度、風力などを含む気象条件、坂の数および顧客からのクレーム数が含まれる。一方、報酬に係る条件には、例えば、ポイント当たりの成果量、金銭金額、感謝報酬などが含まされる。 FIG. 13 shows an example of organized job list data by condition. In this example, for each job J1, J2,..., the job ID is associated with multiple elements included in the conditions related to psychological cost and multiple elements included in the conditions related to remuneration. It shows. Information related to psychological costs includes, for example, responders, area ID, completion date and time, completion deadline, distance from base, weather conditions including weather, temperature, humidity, wind force, etc., number of slopes, and number of complaints from customers. is included. On the other hand, the conditions related to the reward include, for example, the amount of results per point, the monetary amount, and the gratitude reward.
　なお、上記条件別一覧データを生成する際に、コスト／報酬条件整理処理部１５は、上記条件別一覧データの各要素のうち、数値で表される要素以外の各要素を数値化する。例えば、図１４に示すように天候を降水量に、図１５に示すようにエリアＩＤを人口密度に、図１６に示すように感謝報酬を「あり／なし」を示すバイナリ値である“１”，”０”にそれぞれ置換する。同様に、上記条件別一覧データに、必要スキルや社会貢献（ＳＤＧｓ）等が条件の１つとして含まれている場合にも、これらを「あり／なし」を示す“１”，”０”に置換する。 In addition, when generating the above-mentioned condition-based list data, the cost/reward condition arrangement processing unit 15 digitizes each element of the above-mentioned condition-based list data other than the elements expressed by numerical values. For example, as shown in Figure 14, the weather is the amount of precipitation, as shown in Figure 15, the area ID is the population density, and as shown in Figure 16, the gratitude reward is a binary value of "1" indicating "Yes/No". , "0" respectively. Similarly, if the above condition list data includes necessary skills, social contribution (SDGs), etc. as one of the conditions, these can be changed to “1” or “0” to indicate “Yes/No”. Replace.
　コスト／報酬条件整理処理部１５は、上記ジョブの条件別一覧データが新たに生成されるごとにまたは更新されごとに、最新の条件別一覧データを条件別一覧データ記憶部３５に更新記憶する。 The cost/reward condition arrangement processing unit 15 updates and stores the latest condition-specific list data in the condition-specific list data storage unit 35 each time the condition-specific list data of the job is newly generated or updated.
　（２－２）完了済ジョブの抽出
　行動支援制御装置ＳＶの制御部１は、次に完了ジョブ抽出処理部２１の制御の下、ステップＳ２２により上記条件別一覧データ記憶部３５に記憶された条件別一覧データを検索し、過去に完了したジョブを抽出する。 (2-2) Extraction of completed jobs Next, under the control of the completed job extraction processing unit 21, the control unit 1 of the behavior support control device SV extracts the conditions stored in the condition-specific list data storage unit 35 in step S22. Search separate list data and extract jobs completed in the past.
　（２－３）心理的コストを求める報酬ベクトル式の生成
　行動支援制御装置ＳＶの制御部１は、次に心理的コスト判定／決定処理部２２の制御の下、先ずステップＳ２３において、上記条件別一覧データ記憶部３５に記憶された条件別一覧データをもとに、ユーザごとに同一のジョブ条件のもとで対応可能な心理的コストを算出し、その最大値を決定する。 (2-3) Generation of reward vector formula for calculating psychological cost Next, under the control of the psychological cost judgment/determination processing section 22, the control section 1 of the behavior support control device SV first performs the following according to the above conditions in step S23. Based on the condition-specific list data stored in the list data storage unit 35, the psychological cost that can be handled under the same job conditions for each user is calculated, and the maximum value thereof is determined.
　心理的コスト判定／決定処理部２２は、続いてステップＳ２４において、上記条件別一覧データをもとに、ポイント当たりの成果量に相当する値（例えば拠点からの距離）を基準変数とし、この基準変数を表す線形ベクトル式を定義する。または、上記ポイント当たりの成果量を例えば重回帰分析の目的変数とする線形ベクトル式を定義する。 Subsequently, in step S24, the psychological cost judgment/determination processing unit 22 sets a value corresponding to the amount of results per point (for example, distance from the base) as a reference variable based on the above-mentioned condition-specific list data, and sets this criterion as a reference variable. Define a linear vector expression to represent the variable. Alternatively, a linear vector equation is defined in which the amount of results per point is used as the objective variable of multiple regression analysis, for example.
　この場合の線形ベクトル式は、例えば、
　　目的変数（拠点からの距離）＝ａ人口密度＋ｂ降水量＋ｃ温度＋ｄ坂の数＋…＋ｅポイント
と定義される。なお、この時点では完了期限および完了日時は考慮されない。 The linear vector equation in this case is, for example,
Objective variable (distance from base) is defined as: a population density + b precipitation + c temperature + d number of slopes + ... + e points. Note that the completion deadline and completion date and time are not taken into consideration at this point.
　行動支援制御装置ＳＶの制御部１は、次に報酬ベクトル決定処理部２３の制御の下、ステップＳ２５において、ユーザごとにジョブをグループ化する。そして、このグループごとに、上記完了ジョブ抽出処理部２１により抽出された完了済のジョブのうち、基準変数の最大値を目的変数とする重回帰分析を、上記線形ベクトル式を用いて行う。そして、この分析により得られる、ユーザごとの同一のジョブ条件における心理的コストを求めるベクトル式を、ユーザの報酬条件に応じた行動度合いを表す報酬ベクトル式とする。 The control unit 1 of the behavior support control device SV then groups jobs for each user in step S25 under the control of the reward vector determination processing unit 23. Then, for each group, a multiple regression analysis using the maximum value of the reference variables as the objective variable among the completed jobs extracted by the completed job extraction processing unit 21 is performed using the linear vector equation. Then, the vector formula for determining the psychological cost under the same job conditions for each user, obtained through this analysis, is taken as the reward vector formula representing the degree of behavior according to the user's reward condition.
　例えば、報酬ベクトル決定処理部２３は、ユーザの心理的コストを拠点からの距離Ｄとすると、Ｄを
　　Ｄ＝ｄ１人口密度＋ｄ２降水量＋ｄ３温度＋ｄ４坂の数＋…＋ｄ５ポイント＋…
と表す。ここで、ｄ１，ｄ２，…は、説明変数としての各ジョブ条件に対する重み係数を示している。 For example, if the psychological cost of the user is the distance D from the base, then the reward vector determination processing unit 23 calculates D=d1 population density+d2 precipitation+d3 temperature+d4 number of slopes+...+d5 points+...
Expressed as Here, d1, d2, . . . indicate weighting coefficients for each job condition as an explanatory variable.
　（２－４）未完了ジョブに対応可能なユーザの有無の判定
　行動支援制御装置ＳＶの制御部１は、コスト／報酬判定処理部２４の制御の下、先ずステップＳ２６において、上記報酬ベクトル式に未完了ジョブのジョブ条件を説明変数として代入することにより、ユーザごとに想定される心理的コストを算出する。そして、コスト／報酬判定処理部２４は、ステップＳ２７において、算出した上記各ユーザの想定心理的コストを上記未完了ジョブの目的変数とそれぞれ比較することにより、上記未完了ジョブに対応可能なユーザの有無を判定する。 (2-4) Determining whether there is a user who can handle the uncompleted job Under the control of the cost/reward determination processing unit 24, the control unit 1 of the behavior support control device SV first calculates the above reward vector formula in step S26. By substituting the job conditions of uncompleted jobs as explanatory variables, the expected psychological cost for each user is calculated. Then, in step S27, the cost/reward determination processing unit 24 compares the calculated assumed psychological cost of each user with the objective variable of the unfinished job, thereby identifying users who can handle the unfinished job. Determine the presence or absence.
　この判定により、例えば以下の３つの判定パターンのいずれかが得られる。　
　［パターンＡ］；予想心理的コストが目的変数（拠点からの距離）以下となるユーザが１人の場合。つまり、現在の報酬でジョブに対応してくれるユーザが１名のみの場合。　
　［パターンＢ］；予想心理的コストが目的変数（拠点からの距離）以下となるユーザが２人以上の場合。つまり、現在の報酬でジョブに対応してくれるユーザが２名以上の場合。　
　［パターンＣ］；予想心理的コストが目的変数（拠点からの距離）以下となるユーザが１人も存在しない場合。つまり、現在の報酬でジョブに対応してくれるユーザが１名もいない場合。 Through this determination, one of the following three determination patterns is obtained, for example.
[Pattern A]: When there is one user whose expected psychological cost is less than or equal to the objective variable (distance from the base). In other words, if there is only one user who will respond to the job with the current reward.
[Pattern B]: When there are two or more users whose expected psychological cost is equal to or less than the objective variable (distance from the base). In other words, if there are two or more users who can respond to the job with the current reward.
[Pattern C]: A case in which there is no user whose expected psychological cost is equal to or less than the objective variable (distance from the base). In other words, if there is no user who will respond to the job with the current reward.
　（２－５）緊急対応が必要なジョブの判定
　行動支援制御装置ＳＶの制御部１は、続いてジョブ完了状況判定処理部２５の制御の下、ステップＳ２８において、上記条件別一覧データ記憶部３５に記憶された条件別一覧データをもとに、未完了ジョブの完了期限までの残り時間を算出し、算出した上記残り時間をもとに上記未完了ジョブが完了期限の迫っているジョブ、つまり緊急対応が必要なジョブであるか否か判定する。上記完了期限までの残り時間は、完了期限と現在時刻との差として求めることができる。 (2-5) Determination of jobs requiring emergency response Next, in step S28, under the control of the job completion status determination processing unit 25, the control unit 1 of the behavior support control device SV selects the condition-by-condition list data storage unit 35. The remaining time until the completion deadline of the unfinished job is calculated based on the condition-specific list data stored in Determine whether the job requires emergency response. The remaining time until the completion deadline can be determined as the difference between the completion deadline and the current time.
　以上の判定により、未完了ジョブが「緊急対応ジョブ」であるか否かを表す２種類の判定パターンが得られる。この２種類の判定パターンを、ここでは［パターンＤ］および［パターンＥ］と定義する。 Through the above determination, two types of determination patterns are obtained that indicate whether or not the uncompleted job is an "emergency job." These two types of determination patterns are defined here as [pattern D] and [pattern E].
　（３）未完了ジョブに対する最適ユーザの選択とジョブポイントの設定
　行動支援制御装置ＳＶの制御部１は、上記コスト／報酬判定処理部２４および上記ジョブ完了状況判定処理部２５により得られた各判定パターンを組み合わせる。そして、ユーザ選択処理部２７およびポイント修正処理部２６の制御の下で、上記組合せパターンごとに、未完了ジョブに対応させたいユーザの選択と、当該ユーザが未完了ジョブに対し行動を起こしやすくするためのポイントの修正処理を行う。 (3) Selection of optimal user and setting of job points for uncompleted jobs The control unit 1 of the behavior support control device SV performs each judgment obtained by the cost/reward judgment processing unit 24 and the job completion status judgment processing unit 25. Combine patterns. Then, under the control of the user selection processing unit 27 and the point correction processing unit 26, for each of the above combination patterns, the user to be associated with the uncompleted job is selected and the user is made more likely to take action regarding the uncompleted job. Perform point correction processing for this purpose.
　上記ポイントの修正のために、ポイント修正処理部２６は例えば以下の計算式を用いる。　
　　　　（Ｂpt×Ｃpt／Ｄpt）×Ｘａ×Ｙａ×Ｚａ　　　…(1) 
　但し、Ｂptは基準ポイント（例:１pt）、Ｃptは心理的コスト（例：３００ｍ）、Ｄptは１ポイント当たりの成果量（例：１０ｍ）、Ｘａは魅力向上係数（例：２倍）、Ｙａは魅力低下係数（例：０．５倍）、Ｚａは報酬調整係数（例：１．５倍）である。なお、報酬調整係数Ｚａは、ユーザにおけるジョブの魅力を最低限確保する係数である。 To correct the points, the point correction processing section 26 uses, for example, the following calculation formula.
(Bpt×Cpt/Dpt)×Xa×Ya×Za…(1)
However, Bpt is the standard point (e.g. 1pt), Cpt is the psychological cost (e.g. 300m), Dpt is the amount of results per point (e.g. 10m), Xa is the attractiveness improvement coefficient (e.g. 2x), Ya is an attractiveness reduction coefficient (for example, 0.5 times), and Za is a reward adjustment coefficient (for example, 1.5 times). Note that the remuneration adjustment coefficient Za is a coefficient that ensures the minimum attractiveness of the job to the user.
　（３－１）組合せパターンＡ＋Ｄ，Ａ＋Ｅ
　図６は、組合せパターンがＡ＋Ｄ，Ｂ＋Ｅの場合に、ポイント修正処理部２６およびユーザ選択処理部２７が実行するポイント修正処理およびユーザ選択処理の処理手順と処理内容の一例を示すフローチャートである。また、図１７はその処理の一例を説明するための図である。 (3-1) Combination pattern A+D, A+E
FIG. 6 is a flowchart showing an example of the processing procedure and processing contents of the point correction processing and user selection processing executed by the point correction processing section 26 and the user selection processing section 27 when the combination patterns are A+D and B+E. Further, FIG. 17 is a diagram for explaining an example of the processing.
　ポイント修正処理部２６は、ステップＳ３０，Ｓ３２において、上記組合せパターンがＡ＋ＤであるかＡ＋Ｅであるかを判定する。図１７に示す例では、未完了ジョブＪ３に対するユーザＢ，Ｃの報酬ベクトルＩＢ３，ＩＣ３は未完了ジョブＪ３の目的変数に対しＩＢ３LAK ，ＩＣ３LAK だけ不足しているのに対し、ユーザＡの報酬ベクトルＩＡ３は未完了ジョブＪ３の目的変数より高い。従って、この場合未完了ジョブＪ３に対応可能なユーザはＡだけとなる。また、上記未完了ジョブＪ３が緊急対応ジョブでなければ、ポイント修正処理部２６は［パターンＡ＋Ｄ］と判定してステップＳ３１に移行する。このステップＳ３１においてポイント修正処理部２６は、未完了ジョブＪ３に対するユーザＡの報酬ポイントを修正せずにそのまま出力処理部２８に渡す。 The point correction processing unit 26 determines whether the combination pattern is A+D or A+E in steps S30 and S32. In the example shown in FIG. 17, the reward vectors IB3 and IC3 of users B and C for unfinished job J3 are short by IB3 LAK and IC3 LAK with respect to the objective variables of unfinished job J3, whereas the reward vectors of user A are Vector IA3 is higher than the objective variable of incomplete job J3. Therefore, in this case, the only user who can handle the unfinished job J3 is A. Further, if the unfinished job J3 is not an emergency job, the point correction processing unit 26 determines that it is [pattern A+D] and proceeds to step S31. In this step S31, the point correction processing unit 26 passes the reward points of user A for the incomplete job J3 to the output processing unit 28 as is without correction.
　一方、上記未完了ジョブＪ３が緊急対応ジョブだったとする。この場合、ポイント修正処理部２６は［パターンＡ＋Ｅ］と判定し、ステップＳ３３において、ユーザが対応可能な複数のジョブＪ１，Ｊ２，Ｊ３のうち、上記緊急対応ジョブＪ３に対する魅力度合いを他のジョブＪ１，Ｊ２より増加させるため、上記(1) 式を用いてユーザＡの上記緊急対応ジョブＪ３に対する報酬ベクトルＩＡ３のポイントを増加させる。 On the other hand, assume that the unfinished job J3 is an emergency job. In this case, the point correction processing unit 26 determines [pattern A+E], and in step S33, out of the plurality of jobs J1, J2, and J3 that the user can handle, the attractiveness level of the emergency response job J3 is compared with that of other jobs J1. , J2, the points of the reward vector IA3 for user A's emergency response job J3 are increased using the above equation (1).
　図１７に示した例では、ユーザＡが対応可能なすべてのジョブＪ１（１０pt)，Ｊ２（３０pt），Ｊ３（２０pt）の中で、上記緊急対応ジョブＪ３に対する報酬ベクトルＩＡ３のポイントが最も高くなるように、緊急対応ジョブＪ３に対する報酬ベクトルＩＡ３のポイントに魅力向上係数Ｘａを乗算し、これにより緊急対応ジョブＪ３に対する報酬ベクトルＩＡ３のポイントが例えば３１pt以上となるようにポイントを修正する。 In the example shown in FIG. 17, among all the jobs J1 (10 pt), J2 (30 pt), and J3 (20 pt) that user A can handle, the points of the reward vector IA3 for the emergency response job J3 are the highest. The points of the reward vector IA3 for the emergency response job J3 are multiplied by the attractiveness improvement coefficient Xa, thereby modifying the points so that the points of the reward vector IA3 for the emergency response job J3 become, for example, 31 points or more.
　そして、ポイント修正処理部２６は、ステップＳ３４において、上記緊急対応ジョブＪ３に対応可能なユーザＡに対する修正後ポイントを出力処理部２８に渡す。 Then, in step S34, the point correction processing unit 26 passes the corrected points for user A who can handle the emergency response job J3 to the output processing unit 28.
　（３－２）組合せパターンＢ＋Ｄ，Ｂ＋Ｅ
　図７は、組合せパターンがＢ＋Ｄ，Ｂ＋Ｅの場合に、ポイント修正処理部２６およびユーザ選択処理部２７が実行するポイント修正処理およびユーザ選択処理の処理手順と処理内容の一例を示すフローチャートである。また、図１８はその処理の一例を説明するための図である。 (3-2) Combination pattern B+D, B+E
FIG. 7 is a flowchart showing an example of the processing procedure and processing contents of the point correction processing and user selection processing executed by the point correction processing section 26 and the user selection processing section 27 when the combination patterns are B+D and B+E. Further, FIG. 18 is a diagram for explaining an example of the processing.
　ポイント修正処理部２６は、ステップＳ４０，Ｓ４４において、上記組合せパターンがＢ＋ＤであるかＢ＋Ｅであるかを判定する。いま、例えば図１８に示すように、未完了ジョブＪ３に対応可能なユーザがＡ，Ｂ，Ｃの３人で、上記未完了ジョブＪ３は緊急対応ジョブでなかったとする。この場合、先ずユーザ選択処理部２７が、ステップＳ４１において、ジョブＪ３に対し最も低いポイントで対応可能なユーザを選択する。図１８に示した例では、ジョブＪ３に対する対応可能ポイントはユーザＡが最も小さいので、ユーザ選択処理部２７はユーザＡを選択する。 The point correction processing unit 26 determines whether the above combination pattern is B+D or B+E in steps S40 and S44. For example, as shown in FIG. 18, it is assumed that there are three users A, B, and C who can handle the incomplete job J3, and the incomplete job J3 is not an emergency job. In this case, first, in step S41, the user selection processing unit 27 selects a user who can respond to job J3 with the lowest points. In the example shown in FIG. 18, user A has the smallest support points for job J3, so the user selection processing unit 27 selects user A.
　続いてポイント修正処理部２６が、ステップＳ４２において、上記ステップＳ４１により選択されなかったユーザＢ，Ｃの上記ジョブＪ３に対する報酬ベクトルＩＢ３，ＩＣ３のポイントを、その魅力を低下させるために、上記ユーザＡのジョブＪ３に対する報酬ベクトルＩＡ３のポイントより低くなるように減少させる。 Subsequently, in step S42, the point correction processing unit 26 changes the points of the reward vectors IB3 and IC3 for the job J3 of the users B and C, who were not selected in the step S41, to the points of the reward vectors IB3 and IC3 for the user A, who were not selected in the step S41, in order to reduce the attractiveness of the job J3. The points of reward vector IA3 for job J3 are decreased to be lower than the points of reward vector IA3 for job J3.
　図１８に示した例では、ポイント修正処理部２６は、ユーザＢ，ＣのジョブＪ３に対する報酬ベクトルＩＢ３，ＩＣ３のポイントが、ユーザＡのジョブＪ３に対する報酬ベクトルＩＡ３のポイント（１０pt）以下となるように、ユーザＢ，ＣのジョブＪ３に対する現在の報酬ベクトルＩＢ３，ＩＣ３のポイントに魅力低下係数Ｙｂ，Ｙｃを乗算し、その値を低下させる。 In the example shown in FIG. 18, the point correction processing unit 26 adjusts the points of reward vectors IB3 and IC3 for job J3 of users B and C to be less than or equal to the points (10pt) of reward vector IA3 for job J3 of user A. Then, the points of the current reward vectors IB3 and IC3 for the job J3 of users B and C are multiplied by attractiveness reduction coefficients Yb and Yc, and the values are reduced.
　そして、ポイント修正処理部２６は、ステップＳ４３において、上記各ユーザＡ，Ｂ，Ｃに対する上記修正後のポイントを出力処理部２８に渡す。 Then, the point correction processing unit 26 passes the corrected points for each of the users A, B, and C to the output processing unit 28 in step S43.
　一方、上記ステップ４４による判定の結果、未完了ジョブＪ３が緊急対応ジョブだったとする。この場合、先ずポイント修正処理部２６が、ステップＳ４５において、ユーザＡ，Ｂ，Ｃのそれぞれについて、当該ユーザが対応可能なジョブが複数ある場合に、その中で緊急対応ジョブＪ３に対するポイントが最も高くなるように、ユーザＡ，Ｂ，Ｃの上記緊急対応ジョブＪ３に対する報酬ベクトルＩＡ３，ＩＢ３，ＩＣ３のポイントにそれぞれ魅力向上係数Ｘａ，Ｘｂ，Ｘｃを乗じてポイントを修正する。 On the other hand, assume that the result of the determination in step 44 is that the incomplete job J3 is an emergency job. In this case, first, in step S45, the point correction processing unit 26 determines that for each of users A, B, and C, if there are multiple jobs that the user can handle, the point for emergency response job J3 is the highest among them. The points of the reward vectors IA3, IB3, and IC3 for the emergency response job J3 of users A, B, and C are multiplied by attractiveness improvement coefficients Xa, Xb, and Xc, respectively, so that the points are corrected.
　次にユーザ選択処理部２７が、ステップＳ４６において、上記緊急対応ジョブＪ３に対し対応可能なユーザＡ，Ｂ，Ｃの中から、上記緊急対応ジョブＪ３に対する修正後のポイントが最も小さいユーザを選択する。図１８に示した例では、ジョブＪ３に対するユーザＡの修正後ポイント（２０pt×Ｘａ）が最も小さいので、ユーザ選択処理部２７はユーザＡを選択する。 Next, in step S46, the user selection processing unit 27 selects the user who has the smallest points after modification for the emergency response job J3 from among users A, B, and C who can respond to the emergency response job J3. . In the example shown in FIG. 18, the user A's post-correction points (20pt×Xa) for job J3 are the smallest, so the user selection processing unit 27 selects the user A.
　続いてポイント修正処理部２６は、ステップＳ４７において、上記ステップＳ４６により選択されなかったユーザＢ，Ｃの上記ジョブＪ３に対する報酬ベクトルＩＢ３，ＩＣ３のポイントを、その魅力を低下させるために、上記ユーザＡのジョブＪ３に対する報酬ベクトルＩＡ３のポイントより小さくなるように減少させる。 Subsequently, in step S47, the point correction processing unit 26 changes the points of the reward vectors IB3 and IC3 for the job J3 of the users B and C, who were not selected in the step S46, to the points of the reward vectors IB3 and IC3 of the user A, who were not selected in the step S46, in order to reduce the attractiveness of the job J3. The points of the reward vector IA3 for job J3 are decreased to be smaller than the points of the reward vector IA3 for job J3.
　図１８に示した例では、ポイント修正処理部２６は、ユーザＢ，ＣのジョブＪ３に対する報酬ベクトルＩＢ３，ＩＣ３のポイントが、ユーザＡのジョブＪ３に対する報酬ベクトルＩＡ３のポイント（２０pt×Ｘａ）以下となるように、ユーザＢ，ＣのジョブＪ３に対する現在の報酬ベクトルＩＢ３，ＩＣ３のポイントにそれぞれ魅力低下係数Ｙｂ，Ｙｃを乗じてその値を低下させる。 In the example shown in FIG. 18, the point correction processing unit 26 determines that the points of reward vectors IB3 and IC3 for job J3 of users B and C are less than or equal to the points (20pt×Xa) of reward vector IA3 for job J3 of user A. The points of the current reward vectors IB3 and IC3 for job J3 of users B and C are multiplied by attractiveness reduction coefficients Yb and Yc, respectively, to reduce their values.
　最後にポイント修正処理部２６は、ステップＳ４８においてユーザＡ，Ｂ，Ｃに提示する上記修正後のポイントを出力処理部２８に渡す。 Finally, the point correction processing unit 26 passes the corrected points to be presented to the users A, B, and C to the output processing unit 28 in step S48.
　（３－３）パターンＣ＋Ｄ，Ｃ＋Ｅ
　図８は、組合せパターンがＣ＋Ｄ，Ｃ＋Ｅの場合に、ポイント修正処理部２６およびユーザ選択処理部２７が実行するポイント修正処理およびユーザ選択処理の処理手順と処理内容の一例を示すフローチャートである。また、図１９はその処理の一例を説明するための図である。 (3-3) Pattern C+D, C+E
FIG. 8 is a flowchart showing an example of the processing procedure and processing contents of the point correction processing and user selection processing executed by the point correction processing section 26 and the user selection processing section 27 when the combination patterns are C+D and C+E. Further, FIG. 19 is a diagram for explaining an example of the processing.
　ポイント修正処理部２６は、ステップＳ５０，Ｓ５５において、上記組合せパターンがＣ＋ＤであるかＣ＋Ｅであるかを判定する。いま、例えば図１９に示すように、未完了ジョブＪ１，Ｊ２に対応可能なユーザが１人も存在しなかったとする。 In steps S50 and S55, the point correction processing unit 26 determines whether the combination pattern is C+D or C+E. For example, as shown in FIG. 19, it is assumed that there is no user who can handle incomplete jobs J1 and J2.
　先ず、未完了ジョブＪ１，Ｊ２が緊急対応を要するジョブではない場合、ポイント修正処理部２６はステップＳ５０により［パターンＣ＋Ｄ］と判定し、ステップＳ５１に移行する。そして、ステップＳ５１において、ユーザＡ，Ｂ，Ｃごとに、未完了ジョブＪ１，Ｊ２に対する報酬ベクトルのポイントを増加させる。 First, if the incomplete jobs J1 and J2 are not jobs that require emergency response, the point correction processing unit 26 determines that the pattern is [pattern C+D] in step S50, and proceeds to step S51. Then, in step S51, the points of the reward vector for the incomplete jobs J1 and J2 are increased for each of the users A, B, and C.
　図１９に示す例では、ユーザＡの未完了ジョブＪ１，Ｊ２に対する報酬ベクトルＩＡ１，ＩＡ２に報酬調整係数Ｚａ１，Ｚａ２を乗じて、報酬ポイントＩＡ１ADJ ，ＩＡ２ADJ を追加する。同様に、ユーザＢ，Ｃの未完了ジョブＪ２に対する報酬ベクトルＩＢ２，ＩＣ２にはそれぞれ報酬調整係数Ｚｂ，Ｚｃを乗じて、報酬ポイントＩＢ２ADJ ，ＩＣ２ADJ を追加する。この結果、各未完了ジョブＪ１，Ｊ２に対しユーザＡが対応可能となり、また未完了ジョブＪ２に対してはユーザＡ，Ｂ，Ｃが対応可能となる。 In the example shown in FIG. 19, reward vectors IA1 and IA2 for uncompleted jobs J1 and J2 of user A are multiplied by reward adjustment coefficients Za1 and Za2 to add reward points IA1 ADJ and IA2 ADJ . Similarly, reward vectors IB2 and IC2 for uncompleted jobs J2 of users B and C are multiplied by reward adjustment coefficients Zb and Zc, respectively, and reward points IB2 ADJ and IC2 ADJ are added. As a result, user A can respond to each of the unfinished jobs J1 and J2, and users A, B, and C can respond to unfinished job J2.
　次にユーザ選択処理部２７は、上記未完了ジョブＪ１，Ｊ２を対応させる上で最適なユーザを選択する。図１９に示す例では、ジョブＪ１に対してはユーザＡのみが対応可能であるためユーザＡをそのまま選択する。これに対しジョブＪ２については、複数のユーザＡ，Ｂ，Ｃが対応可能である。このため、ユーザＡ，Ｂ，Ｃの中から、未完了ジョブＪ２に対する調整後の報酬ベクトルＩＡ２＋ＩＡ２ADJ ，ＩＢ２＋ＩＢ２ADJ ，ＩＣ２＋ＩＣ２ADJ が最も低いユーザＡを選択する。 Next, the user selection processing unit 27 selects the most suitable user for matching the incomplete jobs J1 and J2. In the example shown in FIG. 19, only user A can handle job J1, so user A is selected as is. On the other hand, a plurality of users A, B, and C can handle job J2. Therefore, from among users A, B, and C, user A is selected whose adjusted remuneration vectors IA2+IA2 ADJ , IB2+IB2 ADJ , and IC2+IC2 ADJ for uncompleted job J2 are the lowest.
　続いてポイント修正処理部２６は、ステップＳ５３において、上記ステップＳ５２により選択されなかったユーザＢ，Ｃの上記ジョブＪ２に対する報酬ベクトルＩＢ２＋ＩＢ２ADJ ，ＩＣ２＋ＩＣ２ADJ が、上記ユーザＡのジョブＪ２に対する報酬ベクトルＩＡ２＋ＩＡ２ADJ より小さくなるように、報酬ベクトルＩＢ２＋ＩＢ２ADJ ，ＩＣ２＋ＩＣ２ADJにそれぞれ魅力低下係数Ｙｂ，Ｙｃを乗算してその値を低下させる。 Subsequently, in step S53, the point correction processing unit 26 changes the reward vectors IB2+IB2 ADJ and IC2+IC2 ADJ for the job J2 of users B and C not selected in the step S52 to the reward vector IA2+IA2 ADJ for the job J2 of the user A. The reward vectors IB2+IB2 ADJ and IC2+IC2 ADJ are multiplied by attractiveness reduction coefficients Yb and Yc, respectively, to reduce their values so that they become smaller.
　最後にポイント修正処理部２６は、ステップＳ５４において、未完了ジョブＪ１，Ｊ２に対する上記各ユーザＡ，Ｂ，Ｃの修正後ポイントを出力処理部２８に渡す。 Finally, in step S54, the point correction processing section 26 passes the corrected points of each of the users A, B, and C for the incomplete jobs J1 and J2 to the output processing section 28.
　一方、上記ステップ５５による判定の結果、未完了ジョブＪ１，Ｊ２のうちジョブＪ２が緊急対応を要するジョブだったとする。この場合、先ずポイント修正処理部２６は、ステップＳ５６において、上記緊急対応ジョブではない場合と同様に、ユーザＡ，Ｂ，Ｃごとに、各未完了ジョブＪ１，Ｊ２に対する報酬ベクトルのポイントを調整し、これにより未完了ジョブＪ１，Ｊ２に対し少なくとも１人のユーザが対応可能にする。 On the other hand, assume that the result of the determination in step 55 is that job J2 among the incomplete jobs J1 and J2 is a job that requires emergency response. In this case, first, in step S56, the point correction processing unit 26 adjusts the points of the reward vector for each incomplete job J1, J2 for each user A, B, C, as in the case where the job is not an emergency response job. , thereby allowing at least one user to respond to the unfinished jobs J1 and J2.
　続いてポイント修正処理部２６は、ステップＳ５７において、未完了ジョブＪ１，Ｊ２に対し対応可能なユーザＡについて、緊急対応ジョブＪ２に対する調整後の報酬ベクトルＩＡ２＋ＩＡ２ADJ が、期限が迫っていないジョブＪ１に対する調整後の報酬ベクトルＩＡ１＋ＩＡ１ADJ がより高くなるように、緊急対応ジョブＪ２に対する報酬ベクトルＩＡ２に魅力向上係数を乗じる。 Subsequently, in step S57, the point correction processing unit 26 determines that the adjusted reward vector IA2+IA2 ADJ for the emergency response job J2 is the same as that for the job J1 whose deadline is not approaching, for the user A who can respond to the incomplete jobs J1 and J2. The remuneration vector IA2 for the emergency response job J2 is multiplied by the attractiveness improvement coefficient so that the adjusted remuneration vector IA1+IA1 ADJ becomes higher.
　次にユーザ選択処理部２７は、ステップＳ５８において、上記緊急対応ジョブＪ２に対し対応可能なユーザＡ，Ｂ，Ｃの中から、緊急対応ジョブＪ２に対する調整後の報酬ベクトルＩＡ２＋ＩＡ２ADJ ，ＩＢ２＋ＩＢ２ADJ ，ＩＣ２＋ＩＣ２ADJ が最も小さいユーザを選択する。図１９に示した例では、ジョブＪ２に対するユーザＡの調整後の報酬ベクトルＩＡ２＋ＩＡ２ADJ （１０pt×Ｚａ２）が最も小さいので、ユーザ選択処理部２７はユーザＡを選択する。 Next, in step S58, the user selection processing unit 27 selects the adjusted remuneration vector for the emergency response job J2 from among the users A, B, and C who can respond to the emergency response job J2. Select the user with the smallest ADJ . In the example shown in FIG. 19, the adjusted reward vector IA2+IA2 ADJ (10pt×Za2) of user A for job J2 is the smallest, so the user selection processing unit 27 selects user A.
　続いてポイント修正処理部２６は、ステップＳ５９において、上記ステップＳ５８により選択されなかったユーザＢ，Ｃの上記ジョブＪ２に対する調整後の報酬ベクトルＩＢ２＋ＩＢ２ADJ ，ＩＣ２＋ＩＣ２ADJ が、上記ユーザＡのジョブＪ２に対する調整後の報酬ベクトルＩＡ２＋ＩＡ２ADJ （１０pt×Ｚａ２）のポイントより低くなるように、上記報酬ベクトルＩＢ２＋ＩＢ２ADJ ，ＩＣ２＋ＩＣ２ADJ にそれぞれ魅力低下係数Ｙｂ，Ｙｃを乗じて報酬ポイントを減少させる。 Subsequently, in step S59, the point correction processing unit 26 determines that the adjusted reward vectors IB2+IB2 ADJ , IC2+IC2 ADJ for the job J2 of the users B and C not selected in the step S58 are adjusted for the job J2 of the user A. The reward points are reduced by multiplying the reward vectors IB2+IB2 ADJ and IC2+IC2 ADJ by attractiveness reduction coefficients Yb and Yc, respectively, so that the points are lower than the points of the subsequent reward vector IA2+IA2 ADJ (10pt×Za2).
　最後にポイント修正処理部２６は、ステップＳ６０において、上記ユーザＡ，Ｂ，Ｃの各未完了ジョブＪ１，Ｊ２に対する上記修正後ポイントを出力処理部２８に渡す。 Finally, the point correction processing unit 26 passes the corrected points for each of the incomplete jobs J1 and J2 of the users A, B, and C to the output processing unit 28 in step S60.
　（４）行動支援情報の出力
　行動支援制御装置ＳＶの制御部１は、上記ユーザＡ，Ｂ，ＣのジョブＪ１，Ｊ２、Ｊ３に対するポイント修正処理が終了すると、出力処理部２８の制御の下、上記コスト／報酬判定処理部２４により算出された、未完了ジョブＪ１，Ｊ２、Ｊ３に対する各ユーザＡ，Ｂ，Ｃの想定心理的コストおよび報酬条件と、上記ポイント修正処理部２６により算出された、未完了ジョブＪ１，Ｊ２、Ｊ３に対する各ユーザＡ，Ｂ，Ｃの修正後ポイントとを含む行動支援情報を生成する。そして、生成した上記行動支援情報を通信Ｉ／Ｆ部４から対応するユーザＡ，Ｂ，Ｃが使用するユーザ端末ＵＴ１，ＵＴ２，ＵＴ３へ送信する。 (4) Output of behavior support information When the point correction process for jobs J1, J2, and J3 of users A, B, and C is completed, the control unit 1 of the behavior support control device SV, under the control of the output processing unit 28, The assumed psychological costs and remuneration conditions of each user A, B, and C for uncompleted jobs J1, J2, and J3, calculated by the cost/reward determination processing unit 24, and the calculated psychological costs and remuneration conditions of each user A, B, and C for the incomplete jobs J1, J2, and J3, calculated by the point correction processing unit 26, Behavior support information including the corrected points of each user A, B, and C for uncompleted jobs J1, J2, and J3 is generated. Then, the generated action support information is transmitted from the communication I/F unit 4 to the user terminals UT1, UT2, UT3 used by the corresponding users A, B, and C.
　これに対し、ユーザＡ，Ｂ，Ｃは、それぞれ自身のユーザ端末ＵＴ１，ＵＴ２，ＵＴ３により上記行動支援情報を受信する。そして、ユーザＡ，Ｂ，Ｃは、受信した行動支援情報に含まれる修正後ポイントをもとに行動対象となる未完了ジョブを選択し、ジョブを実行する。 On the other hand, users A, B, and C receive the behavior support information through their own user terminals UT1, UT2, and UT3, respectively. Users A, B, and C then select an uncompleted job as an action target based on the corrected points included in the received action support information, and execute the job.
　（効果）
　以上述べたように一実施形態では、過去完了ジョブに係る心理的コストおよび報酬条件をもとに、各ユーザが同一の上記条件下で対応可能な心理的コストの最大値を求め、この心理的コストの最大値を用いて、ユーザごとに同一のジョブ条件における心理的コストを求める報酬ベクトル式を生成する。そして、上記報酬ベクトル式を用いて、ユーザと未完了ジョブとの各組合せについてユーザの予想される心理的コストを求め、この予想心理的コストと報酬とを比較して上記未完了ジョブに対応可能なユーザを判定する。そして、この判定結果に基づいて、上記未完了ジョブに対応可能でかつ報酬ポイントが最も低いユーザを選択し、当該ユーザが上記未完了ジョブを選択実行しやすくするためのポイント修正を行い、修正後のポイントを上記ユーザに提示するようにしている。 (effect)
As described above, in one embodiment, the maximum psychological cost that each user can deal with under the same conditions is calculated based on the psychological cost and reward conditions related to past completed jobs, and Using the maximum cost value, a reward vector formula is generated to determine the psychological cost under the same job conditions for each user. Then, using the above reward vector formula, calculate the user's expected psychological cost for each combination of user and uncompleted job, and compare this expected psychological cost with the reward to make it possible to deal with the uncompleted job. Determine the user. Based on this determination result, the user who is able to handle the unfinished job and has the lowest reward points is selected, and points are modified to make it easier for the user to select and execute the unfinished job. We are trying to present the points to the above users.
　従って、未完了ジョブについて、当該未完了ジョブに対する心理的コストが低くかつ報酬ポイントが最も低いユーザにより、上記未完了ジョブが選択実行される確率を高くすることができる。すなわち、管理者にとっては、未完了ジョブを適切なユーザに適切な報酬で実行してもらうことが可能となり、報酬のトータルコストを抑えつつ、業務効率の向上を図ることが可能となる。 Therefore, it is possible to increase the probability that the uncompleted job will be selected and executed by the user who has the lowest psychological cost and the lowest reward points for the uncompleted job. That is, for the administrator, it is possible to have an appropriate user execute an unfinished job for an appropriate reward, and it is possible to improve work efficiency while suppressing the total cost of compensation.
　しかも一実施形態では、対象ジョブが緊急対応ジョブであるか否かを判定し、この判定結果を上記ジョブに対応可能なユーザの判定結果に加味することで、緊急対応ジョブに対する報酬ポイントが他のジョブに対する報酬ポイントより高くなるように報酬ポイントを修正してする。このため、ユーザが対応可能なジョブが複数存在する場合に、当該ユーザが上記複数のジョブの中から上記緊急対応ジョブを選択して実行する確率を高めることができ、これにより緊急対応ジョブを優先的に実行させることが可能となる。 Moreover, in one embodiment, by determining whether or not the target job is an emergency response job and adding this determination result to the determination result of the user who can handle the job, the reward points for the emergency response job are Modify the reward points so that they are higher than the reward points for the job. Therefore, when there are multiple jobs that a user can handle, it is possible to increase the probability that the user will select and execute the emergency response job from among the multiple jobs, thereby giving priority to the emergency response job. It becomes possible to execute the
　さらに一実施形態では、未完了ジョブに対し対応可能なユーザが存在しない場合に、上記未完了ジョブに対する各ユーザの報酬ポイントを高める修正を行ってジョブに対し対応可能なユーザを生成する。そして、生成されたユーザの中から報酬ポイントが最も低いユーザを選択して、当該ユーザが上記未完了ジョブを選択実行しやすくなるようにポイント修正を行っている。このため、未完了ジョブを適切な報酬により高い確率でユーザに選択実行してもらうことが可能となる。 Furthermore, in one embodiment, when there are no users who can respond to an unfinished job, a modification is made to increase the reward points of each user for the unfinished job to generate users who can respond to the job. Then, a user with the lowest reward points is selected from among the generated users, and points are corrected so that the user can more easily select and execute the unfinished job. Therefore, it is possible to have the user select and execute an uncompleted job with a high probability of receiving an appropriate reward.
　［その他の実施形態］
　（１）前記一実施形態では、未完了ジョブに対するユーザの報酬ベクトルのポイント修正処理を、(1) 式に示したポイント修正式を用いて行う場合を例にとって説明した。すなわち、ポイント当たりの成果量に、魅力向上係数Ｘａ、魅力低下係数Ｙａまたは報酬調整係数Ｚａを乗算することにより、ポイント修正を行っている。 [Other embodiments]
(1) In the above-mentioned embodiment, the case where the point correction process of the user's reward vector for an uncompleted job is performed using the point correction formula shown in equation (1) has been described as an example. That is, points are corrected by multiplying the amount of results per point by an attractiveness improvement coefficient Xa, an attractiveness reduction coefficient Ya, or a remuneration adjustment coefficient Za.
　しかし、ポイント修正処理はそれに限るものではなく、ポイント当たりの成果量に、魅力向上係数Ｘａ、魅力低下係数Ｙａまたは報酬調整係数Ｚａを加減算することにより、ポイント修正を行うようにしてもよい。この場合のポイント修正式を以下に示す。 However, the point correction process is not limited to this, and points may be corrected by adding or subtracting an attractiveness improvement coefficient Xa, an attractiveness reduction coefficient Ya, or a remuneration adjustment coefficient Za to the amount of results per point. The point correction formula in this case is shown below.
　　　　（Ｂpt×Ｃpt／Ｄpt）×Ｐａ×Ｑａ×Ｒａ　　　…(2) 
　但し、Ｂptは基準ポイント（例:１pt）、Ｃptは心理的コスト（例：３００ｍ）、Ｄptは１ポイント当たりの成果量（例：１０ｍ）、Ｐａは魅力向上係数（例：１０pt）、Ｑａは魅力低下係数（例：１０pt）、Ｒａは報酬調整係数（例：１０pt）である。なお、報酬調整係数Ｒａは、ユーザにおけるジョブの魅力を最低限確保する係数である。 (Bpt×Cpt/Dpt)×Pa×Qa×Ra…(2)
However, Bpt is the standard point (e.g. 1pt), Cpt is the psychological cost (e.g. 300m), Dpt is the amount of results per point (e.g. 10m), Pa is the attractiveness improvement coefficient (e.g. 10pt), and Qa is the The attractiveness reduction coefficient (e.g. 10pt) and Ra are the reward adjustment coefficients (e.g. 10pt). Note that the remuneration adjustment coefficient Ra is a coefficient that ensures the minimum attractiveness of the job to the user.
　（２）行動支援制御装置ＳＶの制御部１による上記ジョブ情報、ユーザ情報、エリア情報および報酬情報の取得処理は、業務管理装置において情報が新たに生成されるごと、さらに更新されるごとに行われることが望ましいが、その他一定時間間隔または任意のタイミングで行われてもよい。 (2) The above job information, user information, area information, and remuneration information acquisition processing by the control unit 1 of the behavior support control device SV is performed every time information is newly generated in the work management device and each time the information is updated. Although it is preferable that the process be performed at regular intervals, it may be performed at other fixed time intervals or at arbitrary timing.
　（３）前記一実施形態では、ジョブ情報、ユーザ情報、エリア情報および報酬情報の生成および更新処理が業務管理装置で行われる場合を例にとって説明した。しかし、それに限らず、上記ジョブ情報、ユーザ情報、エリア情報および報酬情報の生成および更新処理は、例えば行動支援制御装置ＳＶの制御部１においてその一部または全部が行われるようにしてもよい。 (3) In the above-mentioned embodiment, the case where the job information, user information, area information, and remuneration information generation and update processing is performed by the business management device has been described as an example. However, the present invention is not limited thereto, and part or all of the generation and update processing of the job information, user information, area information, and remuneration information may be performed, for example, in the control unit 1 of the behavior support control device SV.
　（４）前記一実施形態では、対象ジョブが緊急対応ジョブであるか否かを１つの閾値をもとに判定するようにした。しかし、それに限らず、複数の閾値を用いることで、緊急対応ジョブであるか否かの判定に加えて、緊急対応ジョブの緊急度合いをさらに判定し、緊急対応ジョブに対し緊急度合いが高いほどより選択されやすくするようにポイントの修正を行うようにしてもよい。 (4) In the above embodiment, whether or not the target job is an emergency response job is determined based on one threshold value. However, by using multiple threshold values, in addition to determining whether or not it is an emergency response job, the degree of urgency of the emergency response job can be further determined. The points may be modified to make them easier to select.
　一方、ジョブの種類等によっては、未完了ジョブに対する緊急対応ジョブか否かの判定は必ずしも行わなくてもよい。この場合、ポイント修正処理部２６では、ジョブに対応可能なユーザの判定結果のみに基づいてポイント修正処理が行われる。 On the other hand, depending on the type of job, it is not always necessary to determine whether or not the job is an emergency response job for an uncompleted job. In this case, the point correction processing unit 26 performs point correction processing based only on the determination result of the user who can handle the job.
　（５）その他、行動支援制御装置のハードウェア構成およびソフトウェア構成、各機能の処理手順と処理内容、ジョブの種類等についても、この発明の要旨を逸脱しない範囲で種々変形して実施可能である。 (5) In addition, the hardware configuration and software configuration of the behavior support control device, the processing procedures and processing contents of each function, the types of jobs, etc. can be modified in various ways without departing from the gist of the present invention. .
　以上、この発明の実施形態を詳細に説明してきたが、前述までの説明はあらゆる点においてこの発明の例示に過ぎない。この発明の範囲を逸脱することなく種々の改良や変形を行うことができることは言うまでもない。つまり、この発明の実施にあたって、実施形態に応じた具体的構成が適宜採用されてもよい。 Although the embodiments of the present invention have been described above in detail, the above description is merely an illustration of the present invention in all respects. It goes without saying that various improvements and modifications can be made without departing from the scope of the invention. That is, in implementing the present invention, specific configurations depending on the embodiments may be adopted as appropriate.
　要するにこの発明は、上記実施形態そのままに限定されるものではなく、実施段階ではその要旨を逸脱しない範囲で構成要素を変形して具体化できる。また、上記実施形態に開示されている複数の構成要素の適宜な組み合せにより種々の発明を形成できる。例えば、実施形態に示される全構成要素から幾つかの構成要素を削除してもよい。さらに、異なる実施形態に亘る構成要素を適宜組み合せてもよい。 In short, the present invention is not limited to the above-described embodiments as they are, but can be embodied by modifying the constituent elements at the implementation stage without departing from the spirit of the invention. Moreover, various inventions can be formed by appropriately combining the plurality of components disclosed in the above embodiments. For example, some components may be deleted from all the components shown in the embodiments. Furthermore, components from different embodiments may be combined as appropriate.
　１…制御部
　２…プログラム記憶部
　３…データ記憶部
　４…通信Ｉ／Ｆ部
　５…バス
　１１…ジョブ情報取得処理部
　１２…ユーザ情報取得処理部
　１３…エリア情報取得処理部
　１４…報酬情報取得処理部
　１５…コスト／報酬条件整理処理部
　２１…完了ジョブ抽出処理部
　２２…心理的コスト判定／決定処理部
　２３…報酬ベクトル決定処理部
　２４…コスト／報酬判定処理部
　２５…ジョブ完了状況判定処理部
　２６…ポイント修正処理部
　２７…ユーザ選択処理部
　２８…出力処理部
　３１…ジョブ情報記憶部
　３２…ユーザ情報記憶部
　３３…エリア情報記憶部
　３４…報酬情報記憶部
　３５…条件別一覧データ記憶部
  1... Control unit 2... Program storage unit 3... Data storage unit 4... Communication I/F unit 5... Bus 11... Job information acquisition processing unit 12... User information acquisition processing unit 13... Area information acquisition processing unit 14... Reward information acquisition Processing section 15...Cost/reward condition arrangement processing section 21...Completed job extraction processing section 22...Psychological cost judgment/determination processing section 23...Reward vector determination processing section 24...Cost/reward judgment processing section 25...Job completion status judgment processing Units 26...Point correction processing unit 27...User selection processing unit 28...Output processing unit 31...Job information storage unit 32...User information storage unit 33...Area information storage unit 34...Reward information storage unit 35...Condition list data storage unit

Claims (8)

  1. 　業務に対するユーザの行動を報酬ポイントを用いて支援する行動支援制御装置であって、
    　前記業務に対し、前記ユーザの心理的コストおよび報酬に係る複数の条件を関連付けた業務基礎情報を管理する第１の処理部と、
    　前記業務基礎情報に基づいて、前記ユーザごとに、前記業務のうち過去に完了した完了業務に係る前記条件に応じた最大心理的コストを求め、前記最大心理的コストをもとに前記心理的コストと前記条件との関係を表す報酬ベクトル式を生成する第２の処理部と、
    　前記ユーザごとに、前記報酬ベクトル式を用いて、前記業務のうち未完了業務に係る前記条件に対応する前記ユーザの予想心理的コストを求め、各ユーザの前記予想心理的コストを前記未完了業務に係る所定の目的変数と比較することにより、前記未完了業務に対応可能な前記ユーザを判定する第３の処理部と、
    　前記未完了業務に対応可能な前記ユーザに対し、前記予想心理的コストに応じて前記報酬ポイントが最小となるように前記報酬ポイントを調整する第４の処理部と
    　を具備する行動支援制御装置。     An action support control device that supports a user's actions regarding work using reward points,
    a first processing unit that manages basic business information in which a plurality of conditions related to psychological costs and remuneration of the user are associated with the business;
    Based on the work basic information, the maximum psychological cost according to the conditions related to the completed work completed in the past among the work is determined for each user, and the psychological cost is determined based on the maximum psychological cost. a second processing unit that generates a reward vector expression representing the relationship between and the condition;
    For each user, use the reward vector formula to determine the user's expected psychological cost corresponding to the condition related to the uncompleted task among the tasks, and calculate the expected psychological cost of each user by calculating the expected psychological cost of the uncompleted task. a third processing unit that determines the user who is capable of handling the unfinished business by comparing the user with a predetermined objective variable related to the unfinished business;
    and a fourth processing unit that adjusts the reward points for the user who is able to handle the unfinished tasks so that the reward points are minimized according to the expected psychological cost.
  2. 　前記業務基礎情報に基づいて、前記未完了業務が緊急に対応する必要がある緊急対応業務であるか否かを判定する第５の処理部を、さらに具備し、
    　前記第４の処理部は、前記緊急対応業務であるか否かの判定結果に基づいて、前記ユーザが対応可能な前記業務を複数有している場合に、複数の前記業務のうち前記緊急対応業務に対する前記報酬ポイントを緊急対応業務以外の前記業務に対する前記報酬ポイントより大きくするように調整する、請求項１に記載の行動支援制御装置。     further comprising a fifth processing unit that determines, based on the work basic information, whether the unfinished work is an emergency response work that needs to be handled urgently;
    Based on the determination result of whether or not it is the emergency response task, the fourth processing unit selects the emergency response task from among the plurality of tasks when the user has a plurality of the tasks that can be handled. The behavior support control device according to claim 1, wherein the reward points for tasks are adjusted to be larger than the reward points for tasks other than emergency response tasks.
  3. 　前記第４の処理部は、前記未完了業務に対応可能な前記ユーザが１人で、かつ当該未完了業務が前記緊急対応業務の場合に、
    　　前記ユーザが対応可能な複数の前記業務のうち、前記緊急対応業務に対する前記報酬ポイントを前記緊急対応業務以外の前記業務に対する前記報酬ポイントより大きくする処理を行う、
    　請求項２に記載の行動支援制御装置。     When the number of the users who can handle the unfinished business is one, and the unfinished business is the emergency response business, the fourth processing unit is configured to:
    performing a process of making the reward points for the emergency response task larger than the reward points for the task other than the emergency response task among the plurality of tasks that the user can handle;
    The behavior support control device according to claim 2.
  4. 　前記第４の処理部は、前記未完了業務に対応可能な前記ユーザが複数で、かつ当該未完了業務が前記緊急対応業務の場合に、
    　　前記未完了業務に対応可能な複数の前記ユーザの中から、前記予想心理的コストが最小のユーザを選択する処理と、
    　　選択された前記ユーザが対応可能な複数の前記業務のうち、前記緊急対応業務に対する前記報酬ポイントを前記緊急対応業務以外の前記業務に対する前記報酬ポイントより大きくする処理と
    　を行う、請求項２に記載の行動支援制御装置。     When the number of users who can handle the unfinished work is plural and the unfinished work is the emergency response work, the fourth processing unit
    a process of selecting a user with the minimum expected psychological cost from among the plurality of users who can handle the unfinished business;
    3. A process of making the reward points for the emergency response task larger than the reward points for the task other than the emergency response task among the plurality of tasks that the selected user can handle is performed. behavior support control device.
  5. 　前記第４の処理部は、前記未完了業務に対応可能な前記ユーザが存在せず、かつ当該未完了業務が前記緊急対応業務の場合に、
    　　前記未完了業務の対応候補となるユーザの予想心理的コストに調整用ポイントを加えることで当該ユーザを前記未完了業務に対応可能なユーザに変更する処理と、
    　　前記変更により前記未完了業務に対応可能なユーザが複数になった場合に、前記未完了業務に対応可能な複数の前記ユーザの中から、前記調整用ポイントが加算された予想心理的コストが最小のユーザを選択する処理と、
    　　選択された前記ユーザが対応可能な複数の前記業務のうち、前記緊急対応業務に対する前記報酬ポイントを前記緊急対応業務以外の前記業務に対する前記報酬ポイントより大きくする処理と
    　を行う、請求項２に記載の行動支援制御装置。     When the user who can handle the unfinished business does not exist and the unfinished business is the emergency response business, the fourth processing unit performs the following processing:
    a process of adding adjustment points to the expected psychological cost of the user who is a candidate for handling the unfinished work, thereby changing the user into a user who can handle the unfinished work;
    When the number of users who can handle the unfinished business becomes plural due to the change, the expected psychological cost to which the adjustment points are added is the lowest among the plurality of users who can handle the unfinished business. The process of selecting the user of
    3. A process of making the reward points for the emergency response task larger than the reward points for the task other than the emergency response task among the plurality of tasks that the selected user can handle is performed. behavior support control device.
  6. 　前記第４の処理部は、前記業務に対応可能なユーザが複数の場合に、
    　　複数の前記ユーザのうち、前記予想心理的コストが最小のユーザ以外の前記ユーザに対し、当該ユーザの前記業務に対する前記報酬ポイントを、前記予想心理的コストが最小のユーザの前記業務に対する前記報酬ポイントより小さくする処理を行う、
    　請求項４または５に記載の行動支援制御装置。     The fourth processing unit, when there are multiple users who can handle the business,
    Among the plurality of users, the reward points for the task of the user other than the user with the minimum expected psychological cost are the reward points for the task of the user with the minimum expected psychological cost. Perform processing to make the size smaller.
    The behavior support control device according to claim 4 or 5.
  7. 　業務に対するユーザの行動を報酬ポイントを用いて支援する装置が実行する行動支援制御方法であって、
    　前記業務に対し、前記ユーザの心理的コストおよび報酬に係る複数の条件を関連付けた業務基礎情報を管理する第１の過程と、
    　前記業務基礎情報に基づいて、前記ユーザごとに、前記業務のうち過去に完了した完了業務に係る前記条件に応じた最大心理的コストを求め、前記最大心理的コストをもとに前記心理的コストと前記条件との関係を表す報酬ベクトル式を生成する第２の過程と、
    　前記ユーザごとに、前記報酬ベクトル式を用いて、前記業務のうち未完了業務に係る前記条件に対応する前記ユーザの予想心理的コストを求め、求めた各ユーザの前記予想心理的コストを前記未完了業務に係る所定の目的変数と比較することにより、前記未完了業務に対応可能な前記ユーザを判定する第３の過程と、
    　前記未完了業務に対応可能な前記ユーザに対し、前記予想心理的コストに応じて前記報酬ポイントが最小となるように前記報酬ポイントを調整する第４の過程と
    　を具備する行動支援制御方法。     A behavior support control method executed by a device that supports user behavior regarding work using reward points,
    a first step of managing basic business information in which a plurality of conditions related to psychological costs and remuneration of the user are associated with the business;
    Based on the work basic information, the maximum psychological cost according to the conditions related to the completed work completed in the past among the work is determined for each user, and the psychological cost is determined based on the maximum psychological cost. a second process of generating a reward vector expression representing the relationship between and the condition;
    For each user, use the reward vector formula to determine the user's expected psychological cost corresponding to the condition related to the uncompleted task among the tasks, and then calculate the expected psychological cost of each user by substituting the calculated psychological cost for each user. a third step of determining the user who is capable of handling the uncompleted work by comparing it with a predetermined objective variable related to the completed work;
    and a fourth step of adjusting the reward points for the user who is capable of handling the unfinished tasks so that the reward points are minimized according to the expected psychological cost.
  8. 請求項２に記載の前記行動支援制御装置が具備する前記第１の処理部乃至第５の処理部が実行する処理の少なくとも１つを、前記行動支援制御装置が備えるプロセッサに実行させるプログラム。 A program that causes a processor included in the behavior support control device to execute at least one of the processes executed by the first to fifth processing units included in the behavior support control device according to claim 2.
PCT/JP2022/017948 2022-04-15 2022-04-15 Action support control device, method, and program WO2023199522A1 (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003044630A (en) * 2001-08-03 2003-02-14 Business Brain Showa Ota Inc Personnel data management system and personnel data management method, and computer program
JP2005004416A (en) * 2003-06-11 2005-01-06 Shozo Nagata Customer attraction promotion support device and program for called service shop
JP2013140481A (en) * 2012-01-04 2013-07-18 Fujitsu Ltd Program, method, and information processing apparatus

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003044630A (en) * 2001-08-03 2003-02-14 Business Brain Showa Ota Inc Personnel data management system and personnel data management method, and computer program
JP2005004416A (en) * 2003-06-11 2005-01-06 Shozo Nagata Customer attraction promotion support device and program for called service shop
JP2013140481A (en) * 2012-01-04 2013-07-18 Fujitsu Ltd Program, method, and information processing apparatus

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