Action support control device, method and program

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

[Technical field]

[0001] One aspect of the present invention relates to an action support control device, method, and program used to support, for example, a human action. [Background technology]

[0002] The point incentive system is well known as a mechanism for encouraging people to take action. The point incentive system aims to improve employee motivation and retention rates by giving employees salary and other rewards in the form of points, thereby revitalizing the business organization. The following technologies have been proposed as existing technologies for determining incentive points:

[0003] For example, Patent Document 1 describes a method for calculating the distance between exhibits using location information from a terminal, and determining incentive points according to the calculated distance.

[0004] Furthermore, for example, Patent Document 2 describes a system in which a person's health risk is calculated from their behavioral history, and the risk is presented to the person's relatives and friends, which then give the relatives and friends advice to the person, and incentive points are given to the relatives and friends in proportion to the reduction in the person's risk as a result of the advice. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2018-205833 [Patent Document 2] Japanese Patent No. 6687795 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the technologies described in Patent Documents 1 and 2 determine incentive points simply according to travel distance and health risks, making it difficult to give appropriate incentive points to people who work at their own discretion, such as gig workers, whose numbers have been increasing recently.

[0007] Therefore, it has become common to give a uniform, high incentive point (reward) to people who work in such a diversified way. However, this not only increases the total cost of the reward, but also does not necessarily achieve the expected overall work efficiency because there are individual differences in motivation to act even if rewards are given.

[0008] The present invention has been made in light of the above-mentioned circumstances, and aims to provide a technique that enables improvement of business efficiency while suppressing the total cost of remuneration. [Means for solving the problem]

[0009] In order to solve the above problem, one aspect of the action support control device or action support control method of the present invention, when supporting a user's action in a task using reward points, manages basic task information that associates the user's psychological cost and multiple conditions related to rewards with the task, calculates a maximum psychological cost corresponding to the conditions related to completed tasks among the tasks that have been completed in the past for each user based on the basic task information, generates a reward vector equation that represents the relationship between the conditions and the psychological cost based on the maximum psychological cost, calculates an expected psychological cost of the user corresponding to the conditions related to incomplete tasks among the tasks for each user using the reward vector equation, and compares the expected psychological cost of each user thus calculated with a predetermined objective variable related to the incomplete tasks to determine the users who are capable of handling the incomplete tasks, and adjusts the reward points for the users who are capable of handling the incomplete tasks so that the reward points are minimized according to the expected psychological cost.

[0010] According to one aspect of the present invention, the expected psychological cost of each user according to the reward conditions for the incomplete task is calculated, and the expected psychological cost of each user is compared with the reward conditions for the task to determine users who can handle the incomplete task, and reward points are set for the users. In other words, the users who can handle the task and their rewards are determined according to the psychological cost of the user for the relationship between the task and the reward, so that it is possible to have an appropriate user perform each task with an appropriate reward. Effect of the Invention

[0011] That is, according to one aspect of the present invention, it is possible to provide a technology that enables improvement of business efficiency while suppressing the total cost of remuneration. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram showing a schematic configuration of an action support system including an action support control device according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram showing an example of a hardware configuration of an action support control device according to an embodiment of the present invention. [Diagram 3] FIG. 3 is a block diagram showing an example of the software configuration of the action support control device according to an embodiment of the present invention. [Figure 4] FIG. 4 is a flowchart showing an example of a processing procedure and processing content of the basic information acquisition processing executed by the control unit of the action support control device shown in FIG. [Diagram 5] FIG. 5 is a flowchart showing an example of the procedure and contents of various determination processes based on basic information, which are executed by the control unit of the action support control device shown in FIG. [Figure 6] FIG. 6 is a flowchart showing an example of the processing procedure and processing contents of the point setting processing executed by the control unit of the action support control device shown in FIG. 3 when there is one user capable of handling a job. [Figure 7]FIG. 7 is a flowchart showing an example of the procedure and content of a point setting process and a user selection process executed by the control unit of the action support control device shown in FIG. 3 when there are a plurality of users capable of handling a job. [Figure 8] FIG. 8 is a flowchart showing an example of the procedure and content of the point setting process and user selection process executed by the control unit of the action support control device shown in FIG. 3 when there is no user capable of handling a job. [Figure 9] FIG. 9 is a diagram illustrating an example of job information acquired by the basic information acquisition process illustrated in FIG. [Figure 10] FIG. 10 is a diagram showing an example of user information acquired by the basic information acquisition process shown in FIG. [Figure 11] FIG. 11 is a diagram showing an example of area information acquired by the basic information acquisition process shown in FIG. [Figure 12] FIG. 12 is a diagram showing an example of remuneration information acquired by the basic information acquisition process shown in FIG. [Figure 13] FIG. 13 is a diagram showing an example of list data by condition for each job generated by the basic information organizing process shown in FIG. [Figure 14] FIG. 14 is a diagram showing an example of the condition-specific list data shown in FIG. 13 being quantified. [Figure 15] FIG. 15 is a diagram showing list data by condition used to explain an example of the formulation process of the reward vector equation shown in FIG. [Figure 16] FIG. 16 is a diagram showing list data by condition 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. [Figure 17] FIG. 17 is a diagram for explaining an example of the point setting process in the case where there is one user capable of handling the job shown in FIG. [Figure 18] FIG. 18 is a diagram for explaining an example of the point setting process and the user selection process when there are a plurality of users capable of handling the job shown in FIG. [Figure 19]FIG. 19 is a diagram for explaining an example of the point setting process and the user selection process when there is no user capable of handling the job shown in FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0014] [One embodiment] In one embodiment of the present invention, a case will be described in which, for example, a parcel delivery company supports the actions of multiple delivery personnel in relation to delivery work by using an incentive point system. In this example, hereinafter, the delivery personnel will be referred to as users, and the delivery work will be referred to as jobs.

[0015] The type and content of work is not limited to field work such as delivery services, but various examples are possible, such as employees performing clerical work, design work, and production work at home or any other location.

[0016] (Configuration example) (1) System FIG. 1 is a diagram showing a schematic configuration of an action support system including an action support control device according to an embodiment of the present invention.

[0017] The action support system of one embodiment includes an action support control device SV, and enables information communication via a network NW between this action support control device SV and user terminals UT1 to UTn used by multiple users A to N engaged in business, respectively.

[0018] The user terminals UT1 to UTn are used by users to execute jobs, and are configured by, for example, smartphones. Note that, as the user terminals UT1 to UTn, other devices such as wearable terminals, tablet terminals, and personal computers may also be used.

[0019] The network NW includes, for example, a wide area network with the Internet at its core, and an access network for accessing the wide area network. For example, a public communication network using wired or wireless, a LAN (Local Area Network) using wired or wireless, or a CATV (Cable Television) network is used as the access network. Note that when the action support system is operated, for example, within a company or business premises, the network NW may be composed only of an in-house network such as a LAN or wireless LAN.

[0020] (2) Action Support Control Device SV 2 and 3 are block diagrams showing examples of the hardware and software configurations, respectively, of the action support control device SV.

[0021] The action support control device SV is operated by, for example, a delivery company, and is composed of a server computer installed on the web or in the cloud. The action support control device SV has a control unit 1 using a hardware processor such as a central processing unit (CPU), and a storage unit having a program storage unit 2 and a data storage unit 3, and a communication interface (hereinafter, the interface will be referred to as I / F) unit 4 are connected to this control unit 1 via a bus 5.

[0022] Under the control of the control unit 1, the communication I / F unit 4 communicates information with the user terminals UT1 to UTn using a communication protocol defined by the network NW.

[0023] The program storage unit 2 is configured by combining a non-volatile memory such as a solid state drive (SSD) that can be written and read at any time as a storage medium, and a non-volatile memory such as a read only memory (ROM), and stores application programs required for executing various control processes according to an embodiment, in addition to middleware such as an operating system (OS). Hereinafter, the OS and each application program will be collectively referred to as a program.

[0024] The data storage unit 3 is, for example, a combination of a non-volatile 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 equipped with 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-specific list data storage unit 35 as main storage units required to implement one embodiment of the present invention.

[0025] The job information storage unit 31 stores various information related to 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, etc. The delivery history includes, for example, the person in charge and the completion date and time.

[0026] The user information storage unit 32 stores information about each user who is a delivery person as user information. The user information includes information indicating the current location of each user, but may also include skills and achievements for the work, average remuneration, and the like.

[0027] The area information storage unit 33 stores information about 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 in the area, and meteorological conditions such as the current weather, temperature, and humidity.

[0028] The reward information storage unit 34 includes, for example, an achievement amount corresponding to one point, an amount of money, a type of reward other than an amount of money, etc. As the achievement amount, for example, a travel distance is used.

[0029] The condition-based list data storage unit 35 stores condition-based list data in which elements (variables) related to each job are classified into psychological cost and reward conditions. The condition-based list data is created by the control unit 1, which will be described later, based on the job information, user information, area information, and reward information.

[0030] In this example, since the target is field work such as delivery services, the above job information, user information, area information and remuneration information are obtained and condition-specific list data is generated, but when targeting indoor work such as document creation, area information does not necessarily need to be used.

[0031] The control unit 1 has, as processing functions used to implement one embodiment of the present invention, a job information acquisition processing unit 11, a user information acquisition processing unit 12, an area information acquisition processing unit 13, a reward information acquisition processing unit 14, and a cost / reward condition sorting processing unit 15, and further has a completed job extraction processing unit 21, a psychological cost judgment / determination processing unit 22, a reward vector determination processing unit 23, a cost / reward judgment processing unit 24, a job completion status judgment processing unit 25, a point correction processing unit 26, a user selection processing unit 27, and an output processing unit 28.

[0032] These processing units 11 to 15 and 21 to 28 are all realized by causing a hardware processor of the control unit 1 to execute an application program stored in the program storage unit 2 .

[0033] Some or all of the processing units 11 to 15 and 21 to 28 may be realized using hardware such as an LSI (Large Scale Integration) or an ASIC (Application Specific Integrated Circuit).

[0034] The job information indicates attributes related to a job, and is generated, for example, in a business management device (not shown) of a delivery company each time a new job is requested, 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.

[0035] The user information indicates attributes related to a user, and is generated for each user in, for example, a business management device of a delivery service provider, and is updated according to the user's response status 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.

[0036] The area information indicates attributes related to an area, and is generated for each area with a preset range, for example, in a business management device of a delivery company, and is updated in time series according to weather information acquired from a weather information site, for example. 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.

[0037] The remuneration information indicates attributes related to remuneration, and is created by an administrator in the service management device, and updated by the administrator at regular intervals, for example. The remuneration information acquisition processing unit 14 acquires the remuneration information from the service management device via the communication I / F unit 4, and stores the acquired remuneration information in the remuneration information storage unit 34.

[0038] The cost / reward condition sorting processing unit 15 sorts multiple elements (variables) related to each job into conditions related to psychological costs and conditions related to rewards to generate list data, and stores the list data sorted by condition in the condition-specific list data storage unit 35.

[0039] 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 .

[0040] The psychological cost assessment / determination processing unit 22 calculates the psychological cost for previously completed jobs when each user handled the same job conditions based on the condition-specific list data stored in the condition-specific list data storage unit 35, and determines the maximum value.The psychological cost assessment / determination processing unit 22 then defines a linear vector equation that represents a reference variable, using a value equivalent to the amount of performance per point (e.g., distance from a base). Alternatively, it defines a linear vector equation that uses the amount of performance per point as a target variable of, for example, multiple regression analysis.

[0041] The reward vector determination processing unit 23 groups jobs for each user. Then, for each group, an analysis (e.g., multiple regression analysis) is performed using the linear vector formula described above, with the maximum value of the reference variable among the completed jobs as the objective variable, thereby generating a reward vector formula for determining the psychological cost for each user under the same job conditions. In other words, the reward vector determination processing unit 23 formulates the degree of behavior according to the reward conditions for each user.

[0042] The cost / reward determination processor 24 calculates the expected psychological cost for each user by substituting the job conditions of the uncompleted job as explanatory variables into the reward vector formula. Then, the calculated expected psychological cost for each user is compared with the objective variables of the uncompleted job to determine users who can handle the uncompleted job.

[0043] 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 determines whether the uncompleted job is a job whose completion deadline is approaching, i.e., an emergency response job, based on the calculated remaining time.

[0044] The point correction processing unit 26 combines the judgment result of a user capable of handling an incomplete job obtained by the cost / reward judgment processing unit 24 with the judgment result of an emergency response job obtained by the job completion status judgment processing unit 25, and performs processing to correct the points of the user's reward vector for the job for each combination pattern.

[0045] The user selection processing unit 27 selects, for each of the combination patterns, a user who is most suitable for executing the uncompleted job.

[0046] The output processing unit 28 generates action support information including the expected psychological cost and reward condition for the incomplete job calculated by the cost / reward determination processing unit 24, and each user's corrected points for the incomplete job calculated by the point correction processing unit 26. 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.

[0047] (Example of operation) Next, an example of the operation of the action support control device SV configured as above will be described.

[0048] (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 processing executed by the control unit 1 of the action support control device SV.

[0049] (1-1) Acquiring job information When job information is generated or updated in a service management device operated by a delivery company, the generated or updated job information is transmitted from the service management device to the action support control device SV.

[0050] The control unit 1 of the action support control device SV, under the control of the job information acquisition processing unit 11, receives the above job information via the communication I / F unit 4 in step S10, and stores the received job information in the job information storage unit 31.

[0051] 9 shows an example of job information. As shown in the figure, the job information stores a number of elements related to a job, such as the area ID of the job, the user ID of the person in charge, the completion date and time, the distance from the base, the required skills, and the completion deadline, for each job J1, J2, ... corresponding to a delivery destination, linked to a job ID. Note that the elements related to a job are not limited to the above elements, and may include, for example, the type and weight of the delivery item, and can be set arbitrarily.

[0052] (1-2) Acquisition of user information In the service management device, user information is generated for each of the delivery personnel, users A, B, ..., and the user information is updated according to the user's actions. Each time the user information is generated or updated, it is transmitted from the service management device to the action support control device SV.

[0053] In step S11, the control unit 1 of the action support control device SV, under the control of the user information acquisition processing unit 12, receives the above-mentioned user information via the communication I / F unit 4 and stores the received user information in the user information storage unit 32.

[0054] Fig. 10 shows an example of user information. As shown in the figure, the user information is stored for each user A, B, ..., linked to the user ID, and includes a plurality of elements related to the user, such as the latitude and longitude indicating the current location, address, and the number of complaints from customers. Note that the elements related to the user information are not limited to the above example, and may include age, sex, years of experience, performance values, etc., and can be set arbitrarily.

[0055] (1-3) Obtaining area information In the service management device, area information is generated for each predefined area, and this area information is updated, for example, in response to changes in weather conditions. Each time the area information is generated or updated, it is transmitted from the service management device to the action support control device SV.

[0056] In step S12, the control unit 1 of the action support control device SV, under the control of the area information acquisition processing unit 13, receives the above-mentioned area information via the communication I / F unit 4 and stores the received area information in the area information storage unit 33.

[0057] Fig. 11 shows an example of area information. As shown in the figure, the area information stores a number of elements related to the area, such as date, weather, temperature, humidity, number of slopes, etc., linked to the area ID for each area, for example, Ea, Eb, .... Note that the elements related to the area information are not limited to the above example, and may include area, slope gradient and length, etc., and can be set arbitrarily.

[0058] (1-4) Acquisition of remuneration information In the task management device, the remuneration information is managed at regular time intervals, such as days, weeks, months, etc. And, every time the remuneration information is changed, it is transmitted from the task management device to the action support control device SV.

[0059] In step S13, the control unit 1 of the action support control device SV, under the control of the remuneration information acquisition processing unit 14, receives the above-mentioned remuneration information via the communication I / F unit 4, and stores the received remuneration information in the remuneration information storage unit 34.

[0060] Fig. 12 shows an example of reward information. As shown in the figure, the reward information defines multiple elements related to reward, such as the amount of achievement per point, monetary reward, and gratitude reward, and these elements are updated monthly. For example, the distance traveled is used as the amount of achievement.

[0061] (2) Various judgments based on basic information FIG. 5 is a flowchart showing an example of a processing procedure and processing contents of various determination processes based on basic information.

[0062] (2-1) Creating a list of job-related conditions When at least one of the above basic information is updated, the control unit 1 of the action support control device SV, under the control of the cost / reward condition sorting processing unit 15, first sorts the elements related to each job into conditions related to psychological costs and conditions related to rewards in step S21, thereby generating list data by job condition.

[0063] FIG. 13 shows an example of the list data organized by job conditions. In this example, for each job J1, J2, ..., multiple elements included in the conditions related to psychological cost and multiple elements included in the conditions related to remuneration are associated with the job ID. Information related to psychological cost includes, for example, the person in charge, area ID, completion date and time, completion deadline, distance from the base, weather conditions including weather, temperature, humidity, wind force, etc., the number of slopes, and the number of complaints from customers. Meanwhile, conditions related to remuneration include, for example, the amount of achievement per point, monetary amount, gratitude remuneration, etc.

[0064] When generating the condition-specific list data, the cost / reward condition sorting processing unit 15 quantifies each element of the condition-specific list data other than the elements expressed by numerical values. For example, as shown in FIG. 14, the weather is replaced with precipitation, as shown in FIG. 15, the area ID is replaced with population density, and as shown in FIG. 16, the gratitude reward is replaced with binary values ​​"1" and "0" indicating "yes / no". Similarly, when the condition-specific list data includes required skills, social contribution (SDGs), etc. as one of the conditions, these are replaced with "1" and "0" indicating "yes / no".

[0065] The cost / remuneration condition sorting processing unit 15 updates and stores the latest condition-based list data in the condition-based list data storage unit 35 every time the condition-based list data of the job is newly generated or updated.

[0066] (2-2) Extracting completed jobs Next, under the control of the completed job extraction processing unit 21, the control unit 1 of the action support control device SV searches the condition-based list data stored in the condition-based list data storage unit 35 in step S22, and extracts jobs that have been completed in the past.

[0067] (2-3) Generating a reward vector formula for calculating psychological cost Next, under the control of the psychological cost judgment / decision processing unit 22, the control unit 1 of the action support control device SV first calculates, in step S23, the psychological cost that can be managed under the same job conditions for each user based on the condition-specific list data stored in the condition-specific list data storage unit 35, and determines the maximum value thereof.

[0068] Next, in step S24, the psychological cost assessment / decision processing unit 22 defines a linear vector equation expressing a value equivalent to the amount of performance per point (e.g., distance from the base) as a reference variable based on the condition-specific list data, or defines a linear vector equation using the amount of performance per point as a response variable of, for example, multiple regression analysis.

[0069] The linear vector equation in this case is, for example, Objective variable (distance from base) = a population density + b precipitation + c temperature + d number of slopes + ... + e points At this point, the completion deadline and completion date and time are not taken into consideration.

[0070] Next, in step S25, the control unit 1 of the action support control device SV groups jobs for each user under the control of the reward vector determination processing unit 23. Then, for each group, a multiple regression analysis is performed using the linear vector formula, with the maximum value of the reference variable as the objective variable among the completed jobs extracted by the completed job extraction processing unit 21. The vector formula obtained by this analysis for determining the psychological cost for each user under the same job conditions is set as the reward vector formula representing the degree of action according to the user's reward conditions.

[0071] For example, if the psychological cost of the user is the distance D from the base, the reward vector determination processing unit 23 calculates D as follows: D=d1 population density + d2 precipitation + d3 temperature + d4 number of slopes + ... + d5 points + ... Here, d1, d2, ... indicate weighting coefficients for each job condition as explanatory variables.

[0072] (2-4) Determine if there is a user available to handle the uncompleted job The control unit 1 of the action support control device SV, under the control of the cost / reward determination processing unit 24, first calculates the expected psychological cost for each user by substituting the job conditions of the uncompleted job as explanatory variables into the reward vector formula in step S26. Then, in step S27, the cost / reward determination processing unit 24 compares the calculated expected psychological cost of each user with the objective variable of the uncompleted job, thereby determining whether or not there is a user who can handle the uncompleted job.

[0073] This determination results in, for example, one of the following three determination patterns. [Pattern A]: When there is only one user whose expected psychological cost is equal to or less than the objective variable (distance from the base). In other words, when there is only one user who is willing to do 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, when there are two or more users who are willing to do the job with the current reward. [Pattern C]: When there is no user whose expected psychological cost is equal to or less than the objective variable (distance from the base). In other words, when there is no user who is willing to do the job with the current reward.

[0074] (2-5) Identifying jobs that require urgent action Next, in step S28, the control unit 1 of the action support control device SV, under the control of the job completion status determination processing unit 25, calculates the time remaining until the completion deadline of the uncompleted job based on the condition-specific list data stored in the condition-specific list data storage unit 35, and determines whether the uncompleted job is a job whose completion deadline is approaching, in other words, whether it is a job that requires emergency response, based on the calculated remaining time. The time remaining until the completion deadline can be calculated as the difference between the completion deadline and the current time.

[0075] Through the above determination, two types of determination patterns are obtained that indicate whether or not an incomplete job is an “urgent job.” These two types of determination patterns are defined here as [Pattern D] and [Pattern E].

[0076] (3) Selecting the best user for an incomplete job and setting job points The control unit 1 of the action support control device SV combines the respective judgment patterns obtained by the cost / reward judgment processing unit 24 and the job completion status judgment processing unit 25. Then, under the control of the user selection processing unit 27 and the point correction processing unit 26, for each of the combination patterns, it selects a user to be assigned to an incomplete job and performs point correction processing to make it easier for the user to take action on the incomplete job.

[0077] To correct the above points, the point correction processing unit 26 uses, for example, the following calculation formula. (Bpt×Cpt / Dpt)×Xa×Ya×Za …(1) Where, Bpt is the standard point (e.g. 1pt), Cpt is the psychological cost (e.g. 300m), Dpt is the amount of achievement per point (e.g. 10m), Xa is the attractiveness increase coefficient (e.g. 2x), Ya is the attractiveness decrease coefficient (e.g. 0.5x), and Za is the reward adjustment coefficient (e.g. 1.5x). The reward adjustment coefficient Za is the coefficient that ensures the minimum attractiveness of the job to the user.

[0078] (3-1) Combination patterns 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 the user selection processing executed by the point correction processing unit 26 and the user selection processing unit 27 when the combination pattern is A+D, B+E. Also, Fig. 17 is a diagram for explaining an example of the processing.

[0079] In steps S30 and S32, the point correction processing unit 26 judges whether the combination pattern is A+D or A+E. In the example shown in FIG. 17, the reward vectors IB3 and IC3 of the users B and C for the incomplete job J3 are IB3 LAK ,IC3 LAK While the reward vector IA3 of user A is higher than the objective variable of the uncompleted job J3, in this case, A is the only user who can handle the uncompleted job J3. If the uncompleted job J3 is not an emergency response job, the point correction processing unit 26 determines that the pattern is [Pattern A+D] and proceeds to step S31. In step S31, the point correction processing unit 26 passes the reward points of user A for the uncompleted job J3 to the output processing unit 28 as is without correcting them.

[0080] On the other hand, if the uncompleted job J3 is an emergency response job, the point correction processing unit 26 judges the pattern to be [Pattern A+E], and in step S33, in order to increase the attractiveness of the emergency response job J3 among the multiple jobs J1, J2, and J3 that the user can handle, more than the other jobs J1 and J2, the point of the reward vector IA3 for the emergency response job J3 of the user A is increased using the above formula (1).

[0081] In the example shown in FIG. 17, the reward vector IA3 point for the emergency response job J3 is multiplied by an attractiveness improvement coefficient Xa so that the reward vector IA3 point for the emergency response job J3 is the highest among all jobs J1 (10 pts), J2 (30 pts), and J3 (20 pts) that user A can handle, and the reward vector IA3 point for the emergency response job J3 is thereby modified so that the reward vector IA3 point for the emergency response job J3 is, for example, 31 pts or more.

[0082] Then, in step S34, the point correction processing unit 26 passes the corrected points for the user A who can handle the emergency response job J3 to the output processing unit 28.

[0083] (3-2) Combination patterns 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 the user selection processing executed by the point correction processing unit 26 and the user selection processing unit 27 when the combination patterns are B+D and B+E. Also, Fig. 18 is a diagram for explaining an example of the processing.

[0084] In steps S40 and S44, the point correction processing unit 26 judges whether the combination pattern is B+D or B+E. For example, as shown in Fig. 18, assume that there are three users, A, B, and C, who can handle uncompleted job J3, and that the uncompleted job J3 is not an emergency response job. In this case, the user selection processing unit 27 first selects the user who can handle job J3 with the lowest points in step S41. In the example shown in Fig. 18, user A has the lowest available points for job J3, so the user selection processing unit 27 selects user A.

[0085] Next, in step S42, the point correction processing unit 26 reduces the points of the reward vectors IB3, IC3 for the job J3 of users B and C that were not selected in step S41 so that they are lower than the points of the reward vector IA3 for the job J3 of user A, in order to make it less attractive.

[0086] In the example shown in Figure 18, the point correction processing unit 26 multiplies the points of the current reward vectors IB3, IC3 for users B and C's job J3 by attractiveness reduction coefficients Yb, Yc to reduce the values ​​so that the points of the reward vectors IB3, IC3 for users B and C's job J3 are less than or equal to the points of the reward vector IA3 for user A's job J3 (10 pt).

[0087] Then, in step S43, 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.

[0088] On the other hand, suppose that the uncompleted job J3 is an emergency response job as a result of the determination in step 44. In this case, first, in step S45, when there are multiple jobs that each of the users A, B, and C can handle, the point correction processing unit 26 corrects the points by multiplying the points of the reward vectors IA3, IB3, and IC3 of the users A, B, and C for the emergency response job J3 by the attractiveness improvement coefficients Xa, Xb, and Xc, respectively, so that the points for the emergency response job J3 are the highest among the multiple jobs that the users A, B, and C can handle.

[0089] Next, in step S46, the user selection processing unit 27 selects the user with the smallest post-correction points for the emergency response job J3 from among the users A, B, and C who are able to handle the emergency response job J3. In the example shown in Fig. 18, the post-correction points (20pt x Xa) of user A for job J3 are the smallest, so the user selection processing unit 27 selects user A.

[0090] Next, in step S47, the point correction processing unit 26 reduces the points of the reward vectors IB3, IC3 for the job J3 of users B and C that were not selected in step S46 so that they are smaller than the points of the reward vector IA3 for the job J3 of user A, in order to reduce its attractiveness.

[0091] In the example shown in Figure 18, the point correction processing unit 26 multiplies the current points of reward vectors IB3 and IC3 for users B and C's job J3 by attractiveness reduction coefficients Yb and Yc, respectively, to reduce their values ​​so that the points of reward vectors IB3 and IC3 for users B and C's job J3 are less than or equal to the points of reward vector IA3 for user A's job J3 (20pt x Xa).

[0092] 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.

[0093] (3-3) Patterns 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 the user selection processing executed by the point correction processing unit 26 and the user selection processing unit 27 when the combination pattern is C+D, C+E. Also, Fig. 19 is a diagram for explaining an example of the processing.

[0094] 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 the uncompleted jobs J1 and J2.

[0095] First, if the uncompleted jobs J1 and J2 are not jobs that require an emergency response, the point correction processing unit 26 determines the pattern as [Pattern C+D] in step S50 and proceeds to step S51. Then, in step S51, the points of the reward vector for the uncompleted jobs J1 and J2 are increased for each of the users A, B, and C.

[0096] In the example shown in FIG. 19, the reward vectors IA1 and IA2 for the incomplete jobs J1 and J2 of user A are multiplied by the reward adjustment coefficients Za1 and Za2 to obtain the reward points IA1 and IA2. ADJ ,IA2 ADJ Similarly, the reward vectors IB2 and IC2 for the incomplete job J2 of users B and C are multiplied by the reward adjustment coefficients Zb and Zc, respectively, to obtain reward points IB2 ADJ ,IC2 ADJ As a result, user A can handle each of the uncompleted jobs J1 and J2, and users A, B, and C can handle the uncompleted job J2.

[0097] Next, the user selection processing unit 27 selects the most suitable user for handling the uncompleted 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. In contrast, multiple users A, B, and C can handle job J2. Therefore, from among users A, B, and C, the adjusted reward vector IA2+IA2 for uncompleted job J2 is selected. ADJ ,IB2+IB2 ADJ ,IC2+IC2 ADJ Select user A, which has the lowest

[0098] Next, in step S53, the point correction processing unit 26 calculates the reward vector IB2+IB2 for the job J2 of the users B and C who were not selected in step S52. ADJ ,IC2+IC2 ADJ is the reward vector IA2+IA2 for job J2 of user A. ADJ The reward vector IB2+IB2 is smaller. ADJ ,IC2+IC2 ADJ The attractiveness reduction coefficients Yb and Yc are multiplied to reduce the values.

[0099] Finally, in step S54, the point correction processing unit 26 passes the corrected points of the users A, B, and C for the uncompleted jobs J1 and J2 to the output processing unit 28.

[0100] On the other hand, suppose that the job J2 of the uncompleted jobs J1 and J2 is a job that requires an emergency response as a result of the determination in step S55. In this case, first, in step S56, the point correction processing unit 26 adjusts the points of the reward vectors for each of the uncompleted jobs J1 and J2 for each of the users A, B, and C, in the same manner as in the case where the job is not an emergency response job, thereby making it possible for at least one user to respond to the uncompleted jobs J1 and J2.

[0101] Next, in step S57, the point correction processing unit 26 calculates the adjusted reward vector IA2+IA2 for the emergency response job J2 for the user A who can handle the uncompleted jobs J1 and J2. ADJ The adjusted reward vector for job J1, whose deadline is not approaching, is IA1+IA1 ADJ The reward vector IA2 for the emergency response job J2 is multiplied by the attractiveness improvement coefficient so that the reward vector IA2 for the emergency response job J2 is higher.

[0102] Next, in step S58, the user selection processing unit 27 selects, from among the users A, B, and C who can handle the emergency response job J2, the adjusted reward vector IA2+IA2 ADJ ,IB2+IB2 ADJ ,IC2+IC2 ADJ In the example shown in FIG. 19, the adjusted reward vector IA2+IA2 for user A for job J2 is selected. ADJ Since (10pt×Za2) is the smallest, the user selection processor 27 selects user A.

[0103] Next, in step S59, the point correction processing unit 26 calculates the adjusted reward vector IB2+IB2 for the job J2 of the users B and C who were not selected in step S58. ADJ ,IC2+IC2 ADJ is the adjusted reward vector IA2+IA2 for job J2 of user A. ADJ The reward vector IB2+IB2 is set to be lower than (10pt×Za2). ADJ ,IC2+IC2 ADJ The reward points are reduced by multiplying them by the attractiveness reduction coefficients Yb and Yc, respectively.

[0104] Finally, in step S60, the point correction processing unit 26 passes the corrected points for the uncompleted jobs J1 and J2 of the users A, B, and C to the output processing unit 28.

[0105] (4) Output of behavioral support information When the point correction process for the jobs J1, J2, and J3 of the users A, B, and C is completed, the control unit 1 of the action support control device SV generates action support information under the control of the output processing unit 28, the action support information including the assumed psychological costs and reward conditions of each of the users A, B, and C for the incomplete jobs J1, J2, and J3 calculated by the cost / reward determination processing unit 24, and the corrected points of each of the users A, B, and C for the incomplete jobs J1, J2, and J3 calculated by the point correction processing unit 26. Then, the generated action support information is transmitted from the communication I / F unit 4 to the user terminals UT1, UT2, and UT3 used by the corresponding users A, B, and C.

[0106] In response to this, users A, B, and C receive the action support information on their own user terminals UT1, UT2, and UT3, respectively. Then, users A, B, and C select an incomplete job to be acted on based on the post-correction points included in the received action support information, and execute the job.

[0107] (effect) As described above, in one embodiment, the maximum value of the psychological cost that each user can handle under the same conditions is calculated based on the psychological cost and reward conditions for the previously completed jobs, and a reward vector formula is generated to calculate the psychological cost under the same job conditions for each user using the maximum psychological cost.The reward vector formula is then used to calculate the user's expected psychological cost for each combination of user and incomplete job, and the expected psychological cost is compared with the reward to determine a user who can handle the incomplete job.Then, based on the result of this determination, a user who can handle the incomplete 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 incomplete job, and the modified points are presented to the user.

[0108] Therefore, it is possible to increase the probability that an incomplete job will be selected and executed by a user who has a low psychological cost and the lowest reward points for the incomplete job. In other words, it is possible for the manager to have an appropriate user execute the incomplete job with an appropriate reward, thereby improving work efficiency while suppressing the total cost of rewards.

[0109] Moreover, in one embodiment, by determining whether the target job is an emergency response job or not, and taking this determination result into account in the determination result of the user who can handle the job, the reward points for the emergency response job are corrected so that they are higher than the reward points for other jobs. Therefore, when there are multiple jobs that a user can handle, the probability that the user will select and execute the emergency response job from among the multiple jobs can be increased, and thus it becomes possible to execute the emergency response job preferentially.

[0110] Furthermore, in one embodiment, when there is no user capable of handling an incomplete job, a modification is made to increase the reward points of each user for the incomplete job to generate users capable of handling the job. Then, from among the generated users, a user with the lowest reward points is selected, and points are modified so that the user can easily select and execute the incomplete job. This makes it possible for users to select and execute the incomplete job with a high probability by receiving an appropriate reward.

[0111] [Other embodiments] (1) In the above embodiment, the point correction process of the user's reward vector for an incomplete job is performed using the point correction formula shown in (1). That is, the point correction is performed by multiplying the achievement amount per point by the attractiveness improvement coefficient Xa, attractiveness decrease coefficient Ya, or reward adjustment coefficient Za.

[0112] However, the point correction process is not limited to this, and point correction may be performed by adding or subtracting the attractiveness improvement coefficient Xa, attractiveness reduction coefficient Ya, or reward adjustment coefficient Za to the achievement amount per point. The point correction formula in this case is shown below.

[0113] (Bpt×Cpt / Dpt)×Pa×Qa×Ra …(2) Where, Bpt is the standard point (e.g. 1pt), Cpt is the psychological cost (e.g. 300m), Dpt is the amount of achievement per point (e.g. 10m), Pa is the attractiveness improvement coefficient (e.g. 10pt), Qa is the attractiveness reduction coefficient (e.g. 10pt), and Ra is the reward adjustment coefficient (e.g. 10pt). The reward adjustment coefficient Ra is a coefficient that ensures a minimum attractiveness of the job to the user.

[0114] (2) The process of acquiring the above job information, user information, area information and reward information by the control unit 1 of the action support control device SV is desirably performed each time new information is generated or updated in the business management device, but may also be performed at regular time intervals or at any other arbitrary timing.

[0115] (3) In the above embodiment, the generation and update processing of the job information, user information, area information, and reward information is performed in the service management device. However, the present invention is not limited to this, and the generation and update processing of the job information, user information, area information, and reward information may be performed in part or in whole in the control unit 1 of the action support control device SV.

[0116] (4) In the embodiment described above, whether or not the target job is an emergency response job is determined based on one threshold value. However, the present invention is not limited to this. In addition to determining whether or not the target job is an emergency response job, multiple threshold values ​​may be used to further determine the degree of urgency of the emergency response job, and the points may be modified so that the higher the degree of urgency of the emergency response job, the more likely it is to be selected.

[0117] On the other hand, depending on the type of job, etc., it is not always necessary to determine whether the uncompleted job is an emergency 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.

[0118] (5) In addition, the hardware and software configurations of the action support control device, the processing procedures and processing contents of each function, the types of jobs, and the like may be modified in various ways without departing from the spirit and scope of the present invention.

[0119] Although the embodiment of the present invention has been described in detail above, the above description is merely an example of the present invention in every respect. It goes without saying that various improvements and modifications can be made without departing from the scope of the present invention. In other words, in implementing the present invention, specific configurations according to the embodiment may be appropriately adopted.

[0120] In short, this invention is not limited to the above-mentioned embodiment as it is, and in the implementation stage, the components can be modified and embodied without departing from the gist of the invention. In addition, various inventions can be formed by appropriately combining multiple components disclosed in the above-mentioned embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0121] 1...Control unit 2...Program memory section 3. Data storage section 4. Communication I / F section 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 unit 15…Cost / reward condition sorting processing section 21...Completed job extraction processing unit 22... Psychological cost judgment / decision processing section 23...Reward vector determination processing unit 24…Cost / reward determination processing unit 25...Job completion status determination processing unit 26...Point correction processing section 27...User selection processing unit 28...Output processing section 31...Job information storage unit 32...User information storage unit 33...Area information storage unit 34…Reward information storage unit 35...Condition-specific list data storage section

Claims

1. An action assistance control device that supports a user's action for a task by using reward points, A first processing unit that manages task basic information in which a plurality of conditions related to the psychological cost and reward of the user are associated with the task; a second processing unit that calculates a maximum psychological cost according to the conditions for a previously completed task among the tasks for each of the users based on the task basic information, and generates a reward vector formula that represents a relationship between the psychological cost and the conditions based on the maximum psychological cost; a third processing unit that uses the reward vector formula to calculate an expected psychological cost of the user corresponding to the condition related to an uncompleted task among the tasks, for each user, and compares the expected psychological cost of each user with a predetermined objective variable related to the uncompleted task to determine the user who is capable of handling the uncompleted task; a fourth processing unit that adjusts the reward points for the user who can handle the uncompleted task so that the reward points are minimized according to the expected psychological cost; An action support control device comprising:

2. A fifth processing unit is configured to determine whether the incomplete task is an emergency response task that requires an emergency response based on the task basic information, 2. The action support control device according to claim 1, wherein the fourth processing unit adjusts, based on a determination result of whether or not the task is an emergency response task, when the user has a plurality of tasks that they can handle, the reward points for the emergency response task among the plurality of tasks so as to be greater than the reward points for the tasks other than the emergency response task.

3. The fourth processing unit, when there is one user who can handle the uncompleted task and the uncompleted task is the emergency response task, performing a process of setting the reward points for the emergency response task among the plurality of tasks that the user can handle greater than the reward points for the tasks other than the emergency response task; The action support control device according to claim 2 .

4. The fourth processing unit, when there are a plurality of users who can handle the uncompleted task and the uncompleted task is the emergency response task, A process of selecting a user who has the smallest expected psychological cost from among the plurality of users who can handle the uncompleted tasks; A process of setting the reward points for the emergency response task among the plurality of tasks that the selected user can handle greater than the reward points for the tasks other than the emergency response task; The action support control device according to claim 2 , further comprising:

5. The fourth processing unit, when there is no user who can handle the uncompleted task and the uncompleted task is the emergency response task, A process of changing a user who is a candidate for handling the uncompleted task into a user who can handle the uncompleted task by adding an adjustment point to the predicted psychological cost of the user; When the change results in a plurality of users being able to handle the incomplete tasks, a process of selecting a user who has the smallest predicted psychological cost to which the adjustment points are added from among the plurality of users being able to handle the incomplete tasks; A process of setting the reward points for the emergency response task among the plurality of tasks that the selected user can handle greater than the reward points for the tasks other than the emergency response task; The action support control device according to claim 2 , further comprising:

6. The fourth processing unit, when there are a plurality of users who can handle the task, performing a process of making the reward points for the task of a user other than the user having the smallest expected psychological cost among the plurality of users smaller than the reward points for the task of the user having the smallest expected psychological cost; The action support control device according to claim 4 or 5.

7. 1. An action support control method executed by a device that supports a user's action on a task using reward points, comprising: A first step of managing basic information of a task in which a plurality of conditions related to the psychological cost and reward of the user are associated with the task; a second step of calculating, for each user, a maximum psychological cost according to the conditions related to a previously completed task among the tasks based on the task basic information, and generating a reward vector formula expressing a relationship between the psychological cost and the conditions based on the maximum psychological cost; a third step of determining, for each of the users, an expected psychological cost of the user corresponding to the condition related to an uncompleted task among the tasks by using the reward vector formula, and comparing the expected psychological cost of each user thus determined with a predetermined objective variable related to the uncompleted task, thereby determining the user who is capable of handling the uncompleted task; a fourth step of adjusting the reward points for the users who can handle the uncompleted tasks so that the reward points are minimized according to the expected psychological cost; The action support control method includes the steps of:

8. 3. A program for causing a processor included in the action support control device to execute the processes executed by the first to fifth processing units included in the action support control device according to claim 2.

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