Human Resources Matching Device, Human Resources Matching Method, and Human Resources Matching Program

Abstract

To provide a human resource matching device, a human resource matching method, and a human resource matching program with which it is possible to perform matching of a plurality of employees and a plurality of employers taking into account a skill match degree between desires and skills of employees and the required skills of employers, and possible to evaluate risks of dissatisfaction of matching results by the matching.SOLUTION: A human resource matching device acquires, from terminals, a skill list, a required skill list, a desire list, and dissatisfaction risk factor information. The human resource matching device calculates an order of desires of workers with respect to a plurality of places to work and an order of skill match degrees with respect to the plurality of places to work, on the basis of the skill list, the required skill list, and the desire list. From these calculated orders, and by using a plurality of matching algorithms, a matching result, a weighted risk of leaving to work and a weighted risk of failure to receive orders for each matching result, and a harmonic average of these are calculated for each matching algorithm.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a talent matching device, a talent matching method, and a talent matching program. [Background technology]

[0002] In the temporary staffing industry, workers are matched with employers (dispatch destinations). After being assigned to a workplace, there are cases where workers leave or lose their jobs earlier than expected. To avoid such mismatches in personnel, personnel matching devices have been developed. Patent Document 1 discloses a personnel matching device (hereinafter referred to as the "conventional device") that matches job seekers with recruiters, and that includes: personality assessment means for determining the personality assessment results of job seekers and recruiter's organization members based on information regarding personality assessments; inference means for inferring job seekers who are likely to work for the recruiter's organization for a predetermined number of years or more from the personality assessment results of job seekers and recruiter's organization members; and extraction means for extracting job seekers and recruiters who are likely to work for the recruiter's organization for a predetermined number of years or more. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-54726 Summary of the Invention [Problem to be solved by the invention]

[0004] When conventional systems are applied to the temporary staffing business, the following issues arise. Specifically, a workplace has many attributes, such as the type of work and the work location. Because the conditions for each attribute and the priority of attributes vary depending on the circumstances of the worker and the workplace, personality assessment results (personality traits) alone cannot accurately quantify a worker's preference for a workplace. Therefore, conventional systems cannot perform matching that takes into account the worker's accurate preference for a workplace, which could increase the risk of dissatisfaction, such as the worker leaving the temporary staffing agency due to dissatisfaction with the matching results. Furthermore, conventional systems cannot perform matching that takes into account the worker's skills and the required skills of the workplace, which could increase the risk of dissatisfaction, such as the temporary staffing agency losing a contract to provide the worker to the workplace due to the workplace's dissatisfaction with the matching results. Furthermore, conventional systems cannot determine the dissatisfaction risk of at least one of the worker and the workplace, so they may adopt matching results that have a high risk of dissatisfaction.

[0005] The present invention has been made to solve the above-mentioned problems. That is, one of the objects of the present invention is to provide a talent matching device, a talent matching method, and a talent matching program that can match multiple workers with multiple employment opportunities in consideration of the workers' aspirations and the skill match between the workers' skills and the skills required by the employment opportunities, and that can evaluate the risk of dissatisfaction with the matching results. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems, the human resources matching device of the present invention is a human resources matching device that includes an information processing device that matches a plurality of workers provided by a dispatching business to a plurality of employment destinations with the plurality of employment destinations, and the information processing device is configured to: acquire aspiration-related information regarding the aspirations of the plurality of workers to the plurality of employment destinations, skill-match-related information regarding the degree of match between the skills of the plurality of workers and the required skills of the plurality of employment destinations, information on dissatisfaction risk factors of the plurality of workers, and information on dissatisfaction risk factors of the plurality of employment destinations; and calculate a dissatisfaction index that indicates at least one of the dissatisfaction risks of the plurality of workers and the dissatisfaction risks of the plurality of employment destinations regarding the matching results, based on at least one of the set of aspiration-related information and information on dissatisfaction risk factors of the workers, and the set of information on skill-match-related information and information on dissatisfaction risk factors of the employment destinations.

[0007] The human resources matching method of the present invention is a human resources matching method that uses an information processing device to match a plurality of workers provided by a dispatching business to a plurality of employment destinations, and the information processing device acquires aspiration-related information regarding the aspirations of the plurality of workers to the plurality of employment destinations, skill-match-related information regarding the degree of match between the skills of the plurality of workers and the required skills of the plurality of employment destinations, as well as information on dissatisfaction risk factors of the plurality of workers and information on dissatisfaction risk factors of the plurality of employment destinations, and uses at least one matching algorithm based on the aspiration-related information and the skill-match-related information to calculate matching results that are the result of matching the plurality of workers with the plurality of employment destinations for each matching algorithm, and calculates a dissatisfaction index that indicates at least one of the dissatisfaction risk of the plurality of workers and the dissatisfaction risk of the plurality of employment destinations regarding the matching results, based on at least one of the set of information on the aspiration-related information and the dissatisfaction risk factors of the workers, and the set of information on the skill-match-related information and the dissatisfaction risk factors of the employment destinations.

[0008] The human resources matching program of the present invention is a human resources matching program that causes a computer to match a plurality of workers provided by a dispatching agency with a plurality of employment destinations, and causes the computer to acquire aspiration-related information regarding the aspirations of the plurality of workers for the plurality of employment destinations, skill-match-related information regarding the degree of match between the skills of the plurality of workers and the required skills of the plurality of employment destinations, as well as information regarding dissatisfaction risk factors of the plurality of workers and information regarding dissatisfaction risk factors of the plurality of employment destinations, and calculates matching results that are the result of matching the plurality of workers with the plurality of employment destinations for each matching algorithm using at least one matching algorithm based on the aspiration-related information and the skill-match-related information, and executes a process of calculating a dissatisfaction index that indicates at least one of the dissatisfaction risk of the plurality of workers and the dissatisfaction risk of the plurality of employment destinations for the matching results, based on at least one of a set of information regarding the aspiration-related information and the dissatisfaction risk factors of the workers, and a set of information regarding the skill-match-related information and the dissatisfaction risk factors of the employment destinations. [Effects of the Invention]

[0009] According to the present invention, it is possible to match multiple workers with multiple employment opportunities, taking into consideration the workers' aspirations and the skill match between the workers' skills and the skills required by the employment opportunities, and to evaluate the risk of dissatisfaction with the matching results. Note that the effects described herein are not necessarily limited to those described herein, and may be any of the effects described in this disclosure. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a system configuration diagram of a system including a talent matching device according to an embodiment of the present invention. [Figure 2] FIG. 2 is a schematic diagram showing an example of the configuration of a terminal. [Figure 3] FIG. 3 is a diagram illustrating an example of a list of skills stored in the storage device. [Figure 4] FIG. 4 is a diagram for explaining an example of a list of aspirations stored in a storage device. [Figure 5] FIG. 5 is a diagram illustrating an example of a list of required skills stored in the storage device. [Figure 6] FIG. 6 is a schematic diagram showing an example of the configuration of a personnel matching device. [Figure 7] FIG. 7 is a diagram for explaining a skill match list stored in a storage device. [Figure 8] FIG. 8 is a diagram for explaining the skill match rank table stored in the storage device. [Figure 9] FIG. 9 is a diagram for explaining the aspiration rank table stored in the storage device. [Figure 10] FIG. 10 is a diagram for explaining an example of the matching result stored in the storage device. [Figure 11A] FIG. 11A is a diagram showing a parameterized matching result according to the first matching algorithm. [Figure 11B] FIG. 11B is a diagram showing the parameterized matching result by the second matching algorithm. [Figure 11C] FIG. 11C is a diagram showing a parameterized matching result according to the third matching algorithm. [Figure 12] FIG. 12 is a diagram showing an example of a matching information input screen displayed on the display of the terminal. [Figure 13] FIG. 13 is a diagram showing an example of a matching result comparison screen. [Figure 14] FIG. 14 is a flowchart for explaining the process of creating a skill match rank table. [Figure 15] FIG. 15 is a flowchart for explaining the process of creating a preference rank table. [Figure 16] FIG. 16 is a flowchart for explaining the preference rank calculation process. [Figure 17] FIG. 17 is a diagram for explaining the aspiration rank calculation process. [Figure 18]FIG. 18 is a flowchart for explaining the matching process. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all drawings of the embodiments, the same or corresponding parts may be denoted by the same reference numerals.

[0012] The embodiments are examples for explaining the present invention, and some omissions and simplifications have been made as appropriate for clarity of explanation. The present invention can be implemented in various other forms. Unless otherwise specified, each component may be singular or plural.

[0013] In order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings.

[0014] Although various types of information may be described using expressions such as "table," "list," and "record," the various types of information may be expressed using other data structures. For example, various types of information such as "XX table" may be expressed as "XX information." When describing identification information, expressions such as "identification ID," "name," and "name" are used, but these are interchangeable. Furthermore, the expressions for identification information used may be replaced with expressions for other identification information.

[0015] When there are multiple components with the same or similar functions, they may be described using the same reference numeral with different subscripts. When there is no need to distinguish between these multiple components, the subscripts may be omitted.

[0016] In the embodiments, processing performed by executing a program may be described. Here, a computer executes the program using a processor (e.g., a CPU or a GPU) and performs processing defined by the program using storage resources (e.g., a memory) and interface devices (e.g., a communication port). Therefore, the entity performing the processing by executing the program may be the processor. Similarly, the entity performing the processing by executing the program may be a controller, device, system, computer, or node having a processor. The entity performing the processing by executing the program may be any computing unit, and may include a dedicated circuit that performs specific processing. Here, the dedicated circuit may be, for example, an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), or a CPLD (Complex Programmable Logic Device).

[0017] A program may be installed on a computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server may include a processor and storage resources for storing the program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to other computers. In addition, in an embodiment, two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0018] <<Embodiment>> A talent matching device according to an embodiment of the present invention will be described. FIG. 1 is a system configuration diagram of a system including a talent matching device 200 according to an embodiment of the present invention. As shown in FIG. 1, the system includes a terminal 100 and the talent matching device 200. The terminal 100 and the talent matching device 200 are connected via a network NW1 so as to be able to send and receive information to and from each other. Note that a fifth generation mobile communication system (5G (5th Generation)) may be used for sending and receiving (communicating) information between the terminal 100 and the talent matching device 200.

[0019] 2 is a schematic diagram showing an example of the configuration of the terminal 100. The terminal 100 is used by a user (e.g., an employee of a temporary staffing agency). As shown in FIG. 2, the terminal 100 includes a non-volatile storage device 110 that can read and write data, a memory 120 (e.g., RAM), a CPU 130, an input / output interface 140, a network interface 150, and a display 160.

[0020] The storage device 110 holds (stores, stores) a program 111 and a database 112 .

[0021] The CPU 130 loads the program 111 stored in the storage device 110 into the memory 120. The CPU 130 executes the program 111 loaded into the memory 120 to realize various functions of the terminal 100.

[0022] The database 112 includes a skill list 112a, a preference list 112b, a required skill list 112c, and dissatisfaction risk factor information 112d. Details of this information will be described later. The preference list 112b is information for evaluating a worker's preference for a workplace, and may also be referred to as "preference-related information." The preference list 112b may also be referred to as "aspiration level information." The skill list 112a and the required skill list 112c are information for evaluating the degree of match between a worker's skills and the required skills of a workplace, and may also be referred to as "skill match-related information."

[0023] As described above, the program 111 executed by the CPU 130 is loaded into the memory 120, and data used when the CPU 130 executes the program 111 is temporarily stored therein.

[0024] The input / output interface 140 is an interface for connecting operation devices such as a keyboard and a mouse, and a display 160. The network interface 150 is an interface for connecting the terminal 100 to the network NW1. The display 160 does not necessarily have to be included in the terminal 100. For convenience, the display 160 may also be referred to as a "display device."

[0025] FIG. 3 is a diagram illustrating an example of the skill list 112a stored in the storage device 110. As shown in FIG. 3, the skill list 112a includes worker 301 and possessed skills 302 as columns for storing information (values). In the skill list 112a, information corresponding to each column related to the worker's skills is associated with each other and stored as row-based information (records). Specifically, worker 301 stores the name of the worker to be matched. Possessed skills 302 stores the skills possessed by the corresponding worker.

[0026] FIG. 4 is a diagram illustrating an example of the aspiration list 112b stored in the storage device 110. As shown in FIG. 4, the aspiration list 112b includes worker 401, workplace 402, and aspiration level 403 as columns for storing information (values). In the aspiration list 112b, information corresponding to each column regarding the worker's aspirations for a workplace is associated with each other and stored as row-based information (records). Specifically, worker 401 stores the name of the worker to be matched. Employment workplace 402 stores the name of the workplace to be matched. Aspiration level 403 stores information (numeric value) indicating the aspiration level for the workplace.

[0027] FIG. 5 is a diagram illustrating an example of the required skill list 112c stored in the storage device 110. As shown in FIG. 5, the required skill list 112c includes work place 501 and required skills 502 as columns for storing information (values). In the required skill list 112c, information corresponding to each column regarding skills required of workers by work places is associated with each other and stored as row-based information (records). Specifically, the name of the work place to be matched is stored in work place 501. The required skills 502 stores the type of skill required by the corresponding work place.

[0028] Although not shown in the figure, the dissatisfaction risk factor information 112d includes information on dissatisfaction risk factors for multiple workers and information on dissatisfaction risk factors for multiple workplaces. More specifically, the dissatisfaction risk factor information 112d includes each worker's accumulated dissatisfaction level with the temporary staffing business (sometimes referred to as a "temporary staffing agency" or "dispatch source") (the worker's accumulated dissatisfaction level), each worker's applicability, each workplace's accumulated dissatisfaction level with the temporary staffing business (the workplace's accumulated dissatisfaction level), and the workplace's applicability. Each worker's accumulated dissatisfaction level is an index indicating the worker's satisfaction with the temporary staffing business in the matching process to date, and can be created, for example, by a Likert scale questionnaire. The worker's applicability level is an index indicating the degree to which the temporary staffing business wishes the worker not to leave the temporary staffing business. For example, it is a number from 1 to 5, and the applicability level is expressed on a 5-point scale from 1 to 5. The higher the number, the greater the degree to which the temporary staffing business wishes the worker not to leave the temporary staffing business. The accumulated dissatisfaction level of a workplace is an indicator of how satisfied the workplace is with the temporary staffing agency (dispatch source) in the matching process up to now, and can be calculated, for example, by a Likert scale questionnaire. The applicability of a workplace is an indicator of the degree to which the temporary staffing agency wishes to avoid losing the contract with the workplace that provides workers to the workplace, and is, for example, a number from 1 to 5, and the applicability is expressed on a 5-point scale from 1 to 5, with the higher the number, the higher the degree to which the temporary staffing agency wishes to avoid losing the contract with the workplace.

[0029] Fig. 6 is a schematic diagram showing an example configuration of a talent matching device 200. As shown in Fig. 6, the talent matching device 200 includes a non-volatile storage device 210 that can read and write data, a memory 220 (e.g., RAM), a CPU 230, an input / output interface 240, and a network interface 250. For convenience, the device including the CPU 230, the storage device 210, the memory 220, the input / output interface 240, the network interface 250, and the bus 260 is also referred to as an "information processing device." The information processing device may be a plurality of information processing devices or a virtual information processing device built on a cloud.

[0030] The storage device 210 holds (memorizes, stores) a program 211 and a database 212. The CPU 230 loads the program 211 stored in the storage device 210 into the memory 220. The CPU 230 executes the program 211 loaded into the memory 220 to realize various functions of the talent matching device 200.

[0031] The database 212 includes a skill match list 212a, a skill match rank table 212b, a preference rank table 212c, matching results 212d, and parameterized matching results 212e.

[0032] The skill match list 212a and the skill match rank table 212b may also be referred to as "skill match related information." The aspiration rank table 212c may also be referred to as "aspiration related information." The skill match list 212a may also be referred to as "skill match degree information."

[0033] As described above, the program 211 executed by the CPU 230 is loaded into the memory 220, and data used when the CPU 230 executes the program 211 is temporarily stored therein.

[0034] The input / output interface 240 is an interface for connecting operation devices such as a keyboard and a mouse, a display, etc. The network interface 250 is an interface for connecting the talent matching device 200 to the network NW1.

[0035] FIG. 7 is a diagram illustrating the skill match list 212a stored in the storage device 210. As shown in FIG. 7, the skill match list 212a includes worker 701, workplace 702, and skill match degree 703 as columns for storing information (values). In the skill match list 212a, information corresponding to each column regarding the skill match between a worker and a workplace is associated with each other and stored as row-based information (records). Specifically, the worker's name is stored in worker 701. The workplace 702 stores the name of the workplace. The skill match degree 703 stores the skill match degree (numeric value) between the corresponding worker and workplace. The skill match degree can be calculated, for example, by dividing the number of skills of the worker that satisfy the skills required by the workplace by the number of skills required by the workplace.

[0036] FIG. 8 is a diagram illustrating the skill match rank table 212b stored in the storage device 210. As shown in FIG. 8, the skill match rank table 212b includes rank ID 801, worker 802, workplace 803, and skill match rank 804 as columns for storing information (values). In the skill match rank table 212b, information corresponding to each column relating to the rank (rank) of the skill match between the worker and the workplace is associated with each other and stored as information (record) on a row-by-row basis. Specifically, the rank ID 801 stores an identification ID of the information (record). The worker 802 stores the name of the worker. The workplace 803 stores the name of the workplace. The skill match rank 804 stores the rank (rank) of the skill match.

[0037] FIG. 9 is a diagram illustrating the aspiration rank table 212c stored in the storage device 210. As shown in FIG. 9, the aspiration rank table 212c includes columns (columns) for storing information (values): rank ID 901, worker 902, workplace 903, and aspiration rank 904. In the aspiration rank table 212c, information corresponding to each column relating to the aspiration rank (aptitude order) of a worker's workplace is associated with each other and stored as information (records) on a row-by-row basis. Specifically, the rank ID 901 stores an identification ID of the information (record). The worker's name is stored in the worker 902. The workplace 903 stores the name of the workplace. The aspiration rank 904 stores the rank (order) of the aspiration of the corresponding worker's workplace.

[0038] FIG. 10 is a diagram illustrating an example of a matching result 212d stored in the storage device 210. As shown in FIG. 10, the matching result 212d includes a worker 1001 and a workplace 1002 as columns for storing information (values). In the matching result 212d, information corresponding to each column related to the matching result is associated with each other and stored as row-based information (records). Specifically, the worker 1001 stores the name of the worker. The workplace 1002 stores the name of the workplace matched with the corresponding worker. The matching result 212d is created for each matching algorithm and stored in the storage device 210. In this example, for example, three matching algorithms are used, so three matching results 212d are created and stored in the storage device 210.

[0039] 11A to 11C are diagrams illustrating examples of multiple parameterized matching results 212e obtained using multiple matching algorithms. Fig. 11A shows a parameterized matching result 212e1 obtained using a first matching algorithm, Fig. 11B shows a parameterized matching result 212e2 obtained using a second matching algorithm, and Fig. 11C shows a parameterized matching result 212e3 obtained using a third matching algorithm. Note that the first parameterized matching result 212e1 to the third parameterized matching result 212e3 may be referred to as the "parameterized matching results 212e" when there is no need to particularly distinguish between them.

[0040] FIG. 11A is a diagram illustrating an example of parameterized matching result 212e1 based on the first matching algorithm stored in storage device 210. As shown in FIG. 11A, parameterized matching result 212e1 includes, as columns for storing information (values), worker 1101, worker's accumulated dissatisfaction level 1102, worker's applicability 1103, workplace 1104, workplace's accumulated dissatisfaction level 1105, workplace's applicability 1106, aspiration level 1107, skill match level 1108, risk of leaving job (aspiration level) 1109, and risk of losing job (skill) 1110. In first parameterized matching result 212e1, information corresponding to each column related to parameters corresponding to matching result 212d is associated with each other and stored as row-based information (records). Specifically, worker 1101 stores the worker's name. The worker's accumulated dissatisfaction level is stored in the worker's accumulated dissatisfaction level 1102. The worker's applicability level 1103 is stored in the worker's applicability level.

[0041] The name of the workplace of the matching result of the corresponding worker is stored in the workplace 1104. The accumulated dissatisfaction level of the workplace 1105 is stored in the accumulated dissatisfaction level of the workplace. The applicability level of the workplace 1106 is stored in the applicability level of the workplace.

[0042] The degree of aspiration 1107 stores a numerical value indicating the degree of aspiration of the corresponding worker for the workplace. The skill match degree 1108 stores a numerical value indicating the skill match degree of the corresponding worker for the workplace. The risk of leaving (degree of aspiration) 1109 stores a numerical value indicating the risk of leaving (risk of the worker leaving the temporary staffing business) of the corresponding worker. The risk of losing (skill) 1110 stores a numerical value indicating the risk of losing (risk of the temporary staffing business losing a contract to provide the corresponding worker to the workplace) of the corresponding workplace. The details of the information stored in Figures 11B and 11C are the same as those in Figure 11A, so explanations will be omitted.

[0043] <Outline of operation> An overview of the operation of the talent matching device 200 according to an embodiment of the present invention will now be described. The terminal 100 transmits information necessary for matching workers with employers and calculating various parameters for the matching results 212d to the talent matching device 200 via the network NW1 (see FIG. 1). The information necessary for matching and calculating various parameters for the matching results 212d includes, for example, a skill list 112a, aspiration list 112b, required skill list 112c, and dissatisfaction risk factor information 112d.

[0044] 12 shows an example of a matching information input screen GM1 displayed on the display 160 of the terminal 100. The matching information input screen GM1 is a GUI (Graphical User Interface) screen. The matching information input screen GM1 includes a first operation button 1201, a second operation button 1202, a third operation button 1203, a fourth operation button 1204, and a matching start button 1205.

[0045] The first operation button 1201 is a button configured with an image for selecting and deciding on the skill list 112a stored in the storage device 110 of the terminal 100 to be uploaded to the talent matching device 200. The second operation button 1202 is a button configured with an image for selecting and deciding on the preference list 112b stored in the storage device 110 of the terminal 100 to be uploaded to the talent matching device 200. The third operation button 1203 is a button configured with an image for selecting and deciding on the required skill list 112c stored in the storage device 110 of the terminal 100 to be uploaded to the talent matching device 200. The fourth operation button 1204 is a button configured with an image for selecting and deciding on the dissatisfaction risk factor information 112d stored in the storage device 110 of the terminal 100 to be uploaded to the talent matching device 200.

[0046] The matching start button 1205 is a button made up of an image that is operated to start matching. When the matching start button 1205 is operated, the information required for the selected and determined matching is uploaded to the talent matching device 200. The talent matching device 200 starts matching using the uploaded information.

[0047] When the talent matching device 200 starts matching, it calculates a matching result 212d for each matching algorithm and a first parameter-attached matching result 212e1 to a third parameter-attached matching result 212e3.

[0048] The talent matching device 200 displays a matching result comparison screen GM2 on a display device (for example, the display 160 of the terminal 100) based on the matching result with the first parameter 212e1 to the matching result with the third parameter 212e3 and other necessary information. Figure 13 shows an example of the matching result comparison screen GM2.

[0049] As shown in FIG. 13, the matching result comparison screen GM2 includes first information 1301, second information 1302, third information 1303, fourth information 1304, and a button 1305 for selecting a possible workplace.

[0050] The first information 1301 is information about the matching result 212d by the first matching algorithm. The first information 1301 includes the first parameterized matching result 212e1, a weighted turnover risk value calculated based on the first parameterized matching result 212e1, a weighted loss risk value, and a harmonic mean value of these.

[0051] The second information 1302 is information about the matching result 212d by the second matching algorithm. The second information 1302 includes the second parameterized matching result 212e2, a weighted turnover risk value calculated based on the second parameterized matching result 212e2, a weighted loss risk value, and a harmonic mean value thereof.

[0052] The third information 1303 is information related to the matching result 212d by the third matching algorithm. The third information 1303 includes the matching result 212e3 with the third parameters, a weighted turnover risk value calculated based on the matching result 212e3 with the third parameters, a weighted loss risk value, and a harmonic mean value thereof.

[0053] The fourth information 1304 includes information indicating recommended employment proposals. The employment proposal selection button 1305 is a button composed of an image that is operated to select an employment proposal. By viewing the matching result comparison screen GM2, a user (for example, an employee of a temporary staffing agency) can understand the dissatisfaction risk of the matching result 212d and which workers and employment proposals in the matching result 212d have a high dissatisfaction risk (risk of quitting the job and / or risk of losing the job).

[0054] The effects of the human resource matching device 200 described above will now be explained. Staffing agencies deal with a large number of workers and employers, and it is difficult to match the preferences of all workers with the preferences of all employers. Therefore, since a mismatch in preferences can lead to the risk of workers quitting their jobs or employers losing the job, it is desirable to select matching results after visualizing the risk of dissatisfaction between workers and employers due to a mismatch in preferences. However, conventional technology was unable to estimate the high risk of dissatisfaction between workers and employers for each matching result.

[0055] In contrast, the talent matching device 200 according to the embodiment uses multiple matching algorithms (three matching algorithms in this example) to match multiple workers with multiple employment opportunities, and calculates multiple matching results 212d for each of the multiple matching algorithms. By using multiple different matching algorithms, multiple matching results are calculated to obtain the optimal matching result. The talent matching device 200 evaluates the dissatisfaction risk for the matching results 212d and prioritizes the matching results 212d to make it easier to select a matching result 212d from the multiple matching results 212d.

[0056] In the dissatisfaction risk assessment, the talent matching device 200 quantifies and visualizes the dissatisfaction risk of each worker and each employment location. The talent matching device 200 presents the visualized data (image) to the user of the staffing agency, for example by displaying it on the display 160 (display device) of the terminal 100. By viewing the image, the user of the staffing agency can see which workers and employment locations are highly dissatisfied with the staffing agency from the matching results 212d. This allows the talent matching device 200 to urge the staffing agency to provide support to the highly dissatisfied workers and employment locations, thereby reducing the risk of workers quitting their jobs and the risk of employers losing their jobs.

[0057] Furthermore, the human resources matching device 200 calculates dissatisfaction indices (weighted risk of job turnover, weighted risk of job loss, and harmonic mean) indicating the dissatisfaction risk for the matching result 212d using the worker's dissatisfaction risk (risk of job turnover) and the employer's dissatisfaction risk (risk of job loss), and prioritizes the multiple matching results 212d based on the dissatisfaction indices so that the matching results 212d with lower dissatisfaction indices have a higher priority.The human resources matching device 200 determines recommended matching results 212d with lower dissatisfaction indices based on the priorities of the multiple matching results 212d, and presents these to the staffing business, thereby encouraging the staffing business to select (hire) matching results 212d with lower dissatisfaction risk.

[0058] <Specific operation> The specific operation of the talent matching device 200 according to the embodiment of the present invention will now be described. Fig. 14 is a flowchart for explaining the process of creating the skill match rank table 212b. When matching begins, the CPU 230 of the talent matching device 200 starts processing from step 1400, and after sequentially executing the processes of steps 1405 to 1415 described below, proceeds to step 1495 and temporarily ends this processing flow.

[0059] Step 1405: The CPU 230 calculates the skill match list 212a based on the skill list 112a and the required skill list 112c uploaded from the terminal 100, thereby obtaining the skill match list 212a and storing it in the database 212.

[0060] Step 1410: The CPU 230 ranks each place of employment based on the skill match list 212a.

[0061] Step 1415: The CPU 230 creates a skill match rank table 212 b for the employer based on the ranking results and stores the table in the database 212 .

[0062] 15 is a flowchart for explaining the process of creating the aspiration rank table 212c. When matching begins, the CPU 230 of the talent matching device 200 starts processing from step 1505, and after sequentially executing the processes of steps 1505 to 1515 described below, proceeds to step 1595 and temporarily ends this processing flow.

[0063] Step 1505: The CPU 230 acquires the application list 112b uploaded from the terminal 100.

[0064] Step 1510: The CPU 230 uses the aspiration list 112b to rank each worker. Specifically, the CPU 230 ranks each worker by executing the aspiration rank creation process shown in Fig. 16. Details of the aspiration rank creation process will be described later.

[0065] Step 1515: The CPU 230 creates a worker preference ranking table 212c based on the ranking results and stores it in the database 212.

[0066] Fig. 16 is a flowchart for explaining the preference rank calculation process. When the CPU 230 of the talent matching device 200 proceeds to step 1510 in Fig. 15, it starts processing from step 1600, executes the processing of steps 1605 to 1625 described below in order, then proceeds to step 1695 to temporarily end this processing flow, and proceeds to step 1515 in Fig. 15.

[0067] Step 1605: CPU 230 calculates the average aspiration level for each job (place of employment). As shown in table 1700 in Fig. 17, for example, if the place of employment is suburban call center operator, the average aspiration level is calculated by adding up the aspiration levels for each worker corresponding to the suburban call center operator and then dividing the total by the number of workers. The average aspiration levels are calculated similarly for other jobs (places of employment (suburban general office worker, suburban restaurant hall staff, urban general office worker, urban call operator)).

[0068] Step 1610: The CPU 230 calculates the difference between the preference and the average preference for each job by subtracting the average preference from the corresponding preference, as shown in Fig. 17 .

[0069] Step 1615: The CPU 230 uses the difference from the average preference for each job to sort the jobs so that the larger the difference, the higher the rank, as shown in FIG.

[0070] Step 1620: The CPU 230 sorts the applications by the degree of preference, as shown in FIG. 17, so that the higher the degree of preference, the higher the rank.

[0071] Step 1625: The CPU 230 derives an aspiration rank for each worker based on the results of the processing in steps 1615 and 1620, as shown in FIG.

[0072] Fig. 18 is a flowchart for explaining the matching process. When the CPU 230 of the talent matching device 200 completes the process of creating the skill match rank table 212b in Fig. 14 and the process of creating the aspiration rank table 212c in Fig. 15, it starts processing from step 1800, and after sequentially executing the processes of steps 1805 to 1840 described below, proceeds to step 1895 and temporarily ends this processing flow.

[0073] Step 1805: The CPU 230 acquires from the database 212 the skill match rank table 212b created by the process of creating the skill match rank table 212b and the aspiration rank table 212c created by the process of creating the aspiration rank table 212c.

[0074] Step 1810: The CPU 230 performs matching using the acquired skill match rank table 212b and aspiration rank table 212c. This matching is performed using the first matching algorithm to the third matching algorithm.

[0075] Examples of the first matching algorithm and the second matching algorithm are algorithms that apply the Gale-Shapley algorithm. The first matching algorithm and the second matching algorithm are modifications of the application method of the Gale-Shapley algorithm.

[0076] The Gale-Sharpley algorithm is an algorithm used to solve stable marriage problems. It is an algorithm that can stably match men and women in a group of men and women with a prioritized list. Specifically, the Gale-Sharpley algorithm is an algorithm in which a man proposes to the woman he likes the most who has not been rejected, and a woman matches with a man who proposes to her unless she receives a proposal from a man she likes more. It is known to result in the optimal match for the man.

[0077] By applying this algorithm to matching, it is possible to stably match multiple prioritized workers (i.e., workers with aspiration ranks) with prioritized workplaces (i.e., multiple workplaces with skill match ranks) (i.e., stable matching can be achieved by taking into account the worker's aspirations and the skill match between the worker's skills and the required skills of the workplace).

[0078] The first matching algorithm and the second matching algorithm differ in that they select either the worker or the employer as the male side, with the first matching algorithm selecting the employer as the male side and the second matching algorithm selecting the worker as the male side. Therefore, the first matching algorithm results in a matching result in which the employer's preferences are prioritized, while the second matching algorithm results in a matching result in which the worker's preferences are prioritized.

[0079] The third matching algorithm is an algorithm that can perform matching that compromises the preferences of employers and workers. The third matching algorithm calculates the harmonic mean of the preference levels (skill match and aspiration) of employers and workers, and matches are made in descending order of the harmonic mean. Note that the third matching algorithm ignores matches that overlap with existing matches in either the employer or worker.

[0080] Step 1815: The CPU 230 obtains the matching results 212d for each matching algorithm calculated in step 1810, and stores them in the database 212. That is, the CPU 230 obtains three matching results 212d for each of the first to third matching algorithms, and stores them in the database 212.

[0081] Step 1820: The CPU 230 calculates the risk of turnover for each worker in the matching result 212d and the risk of losing the job for each employment destination. The risk of turnover is the risk that a worker will leave the temporary staffing agency (dispatch source), and is one of the indicators for evaluating matching. The CPU 230 calculates the risk of turnover based on the worker's accumulated dissatisfaction level and aspiration level. For example, the CPU 230 calculates the risk of turnover by applying the worker's accumulated dissatisfaction level and aspiration level to calculation formula (1).

[0082] Risk of leaving a job = (5 - aspiration) + employee's accumulated dissatisfaction coefficient x employee's accumulated dissatisfaction...Formula (1) The coefficient of the worker's accumulated dissatisfaction level in formula (1) is a predetermined value that is set in advance. This allows the CPU 230 to calculate the risk of each worker leaving the temporary staffing agency, which indicates the risk that each worker in the matching result 212d will leave the temporary staffing agency.

[0083] The degree of aspiration is obtained from the aspiration list 112c uploaded from the terminal 100 to the talent matching device 200, and the worker's accumulated dissatisfaction degree is obtained from the dissatisfaction risk factor information 112d uploaded from the terminal 100 to the talent matching device 200.

[0084] The risk of losing a contract is the risk that a staffing agency (dispatch source) will lose a contract to provide a worker to a dispatch destination (place of employment), and is one of the indicators for evaluating matching. The CPU 230 calculates the risk of losing a contract based on the accumulated dissatisfaction level and skill match level with the place of employment. For example, the CPU 230 calculates the risk of losing a contract by applying the accumulated dissatisfaction level and skill match level with the place of employment to formula (2).

[0085] Risk of losing a job = (5 - Skill Match) + (Employer's Accumulated Dissatisfaction Coefficient x Employer's Accumulated Dissatisfaction)...Formula (2) The coefficient of accumulated dissatisfaction with the workplace in formula (2) is a predetermined value that is set in advance. This allows the CPU 230 to calculate the risk of losing each employment in the matching results 212d, which indicates the risk that each dispatching business will lose a contract with an employment destination that provides workers to the employment destination.

[0086] Step 1825: The CPU 230 creates matching results 212e1 to 212e3 with employee turnover risk and job loss risk values ​​(i.e., matching result 212e1 with the first parameter to matching result 212e3 with the third parameter) based on the dissatisfaction risk factor information 112d uploaded from the terminal 100, the matching result 212d, and the employee turnover risk and job loss risk of each employer calculated in step 1820.

[0087] Step 1830: The CPU 230 calculates the weighted turnover risk, weighted loss risk, and harmonic mean of the weighted turnover risk and weighted loss risk for each matching result 212d (each parameterized matching result 212e (first parameterized matching result 212e1 to third parameterized matching result 212e3)).

[0088] The weighted employee turnover risk is calculated based on the employee turnover risk and the employee's applicability calculated in step 1820. Specifically, the CPU 230 calculates the weighted employee turnover risk by summing the value of each employee's employee turnover risk multiplied by the applicability for each of the parameterized matching results 212e1 to 212e3.

[0089] The weighted risk of losing the job is calculated based on the risk of losing the job and the applicability of the employer calculated in step 1820. Specifically, the CPU 230 calculates the weighted risk of losing the job by summing the value of the risk of losing the job multiplied by the applicability of each worker in each of the first parameter-attached matching result 212e1 to the third parameter-attached matching result 212e3. Furthermore, the CPU 230 calculates the harmonic mean of the weighted risk of quitting the job and the weighted risk of losing the job for each matching result 212d.

[0090] Step 1835: The CPU 230 prioritizes the matching results 212d. For example, the CPU 230 prioritizes the matching results 212d so that the matching results 212d with the smallest harmonic mean are given priority. By prioritizing based on the harmonic mean, prioritization is performed taking into account both the weighted turnover risk and the weighted lost-bid risk. Note that the CPU 230 may determine the matching result 212d with the highest priority (i.e., the matching result 212d with the smallest harmonic mean) as the recommended matching result 212d.

[0091] Step 1840: The CPU 230 displays a matching result comparison screen GM2 including an image showing information based on the first parameter-attached matching result 212e1 through the third parameter-attached matching result 212e3 and the calculated weighted turnover risk, weighted job loss risk, and harmonic mean for each matching result 212d. As described above, by viewing the matching result comparison screen GM2, a user (e.g., an employee of a temporary staffing agency) can confirm matching results 212d between multiple workers and multiple employers, the weighted turnover risk, weighted job loss risk, and harmonic mean for each matching result 212d, and recommended employers. By viewing the matching result comparison screen GM2, the user can consider the risk of dissatisfaction between the worker and the employer and select (adopt) a matching result 212d with a low dissatisfaction risk.

[0092] <Effects> As described above, the talent matching device 200 according to an embodiment of the present invention can perform stable matching by taking into consideration the worker's aspirations and the skill match between the worker's skills and the skills required by the employer, and can also evaluate the dissatisfaction risk of the matching result 212d resulting from the matching. The talent matching device 200 can select the matching result 212d with the lowest dissatisfaction risk from among multiple matching results 212d of multiple matching algorithms.

[0093] <<Modifications>> The present invention is not limited to the above-described embodiment, and various modifications can be adopted within the scope of the present invention.

[0094] In the above embodiment, the human resources matching device 200 uses multiple matching algorithms to calculate multiple matching results 212d, the weighted turnover risk, the weighted loss risk, and their harmonic mean for each matching result 212d, but it may also be configured to use one matching algorithm to calculate one matching result 212d, the weighted turnover risk, the weighted loss risk, and their harmonic mean for one matching result 212d.

[0095] In the above embodiment, any one or two of the weighted turnover risk, the weighted job loss risk, and the harmonic mean thereof may be calculated for the matching result 212d. At least one of the weighted turnover risk, the weighted job loss risk, and the harmonic mean thereof is an index indicating the dissatisfaction risk of at least one of the workers and the employers of the matching result 212d. For convenience, the index indicating the dissatisfaction risk of at least one of the workers and the employers of the matching result 212d may also be referred to as the "dissatisfaction index."

[0096] In the above embodiment, the weighted turnover risk, weighted deal loss risk, and harmonic mean were calculated for the matching result 212d, but instead of the weighted turnover risk, another index indicating the risk that a worker for the matching result 212d will leave the staffing business may be calculated, and instead of the weighted deal loss risk, another index indicating the risk that the staffing business will lose a contract with a workplace for the matching result 212d may be calculated, and these other harmonic means may be calculated. The weighted turnover risk and other indexes instead of the weighted turnover risk may also be referred to as "turnover risk indexes." The weighted deal loss risk and other indexes instead of the weighted deal loss risk may also be referred to as "decision loss risk indexes."

[0097] In the above embodiment, in step 1835, the CPU 230 may prioritize the matching results 212d based on the weighted turnover risk or the weighted loss risk, so that the matching results 212d with a lower dissatisfaction risk are given priority.

[0098] In the above embodiment, the human resources matching device 200 determined the matching result 212d with the lowest harmonic mean as the recommended matching result 212d based on the harmonic mean, but it may also determine the matching result 212d with the lowest weighted turnover risk as the recommended matching result 212d based only on the weighted turnover risk.

[0099] Furthermore, the talent matching device 200 may determine the matching result 212d with the lowest weighted risk of losing the contract as the recommended matching result 212d based on the weighted risk of losing the contract. The talent matching device 200 may be configured to allow the criteria for determining the recommended matching result 212d to be specified (selected) based on input from an external device such as the terminal 100.

[0100] The talent matching device 200 may display an image indicating the priority order of the multiple matching results 212d on the display device.

[0101] In the above embodiment, the aspiration rank table 212c is created by calculating the aspiration rank table 212c based on the aspiration list 112b, but the method for creating the aspiration rank table 212c is not limited to this and may be created by other methods. In the above embodiment, the skill match list 212a is created based on the skill list 112a and the required skill list 112c, and the skill match rank table 212b is created based on the skill match list 212a, but the method for creating the skill match rank table 212b is not limited to this and may be created by other methods.

[0102] In the above embodiment, the talent matching device 200 may perform a worker dissatisfaction risk assessment that evaluates each worker's dissatisfaction risk with respect to the matching results based on the aspiration-related information and information on worker dissatisfaction risk factors, and a workplace dissatisfaction risk assessment that evaluates each workplace's dissatisfaction risk with respect to the matching results based on the skill-match-related information and information on workplace dissatisfaction risk factors, and calculate a dissatisfaction index using the assessment results. An example of the worker dissatisfaction risk assessment is performed by calculating the worker's turnover risk, as described above. However, it may also be performed by calculating other parameters that represent the risk of the worker leaving the staffing business, based on the aspiration-related information and information on worker dissatisfaction risk factors. An example of the workplace dissatisfaction risk assessment is performed by calculating the workplace's loss risk, as described above. However, it may also be performed by calculating other parameters that represent the risk of the staffing business losing a contract with a workplace to which the staffing business provides a worker, based on the skill-match-related information and information on workplace dissatisfaction risk factors.

[0103] The present invention can also have the following configuration.

[0104] A human resources matching method using an information processing device that matches a plurality of workers provided by a dispatching business to a plurality of employment destinations, comprising: By the information processing device, Acquire aspiration-related information relating to the aspirations of the plurality of workers for the plurality of workplaces, skill-match-related information relating to the degree of match between the skills of the plurality of workers and the skills required by the plurality of workplaces, as well as information on dissatisfaction risk factors of the plurality of workers and information on dissatisfaction risk factors of the plurality of workplaces; Using at least one matching algorithm based on the aspiration-related information and the skill-match-related information, calculate matching results that are results of matching between the plurality of workers and the plurality of employment opportunities for each matching algorithm; calculate a dissatisfaction index indicating at least one of a plurality of dissatisfaction risks of the workers and a plurality of dissatisfaction risks of the employers with respect to the matching results, based on at least one of a set of the aspiration-related information and information on dissatisfaction risk factors of the workers, and a set of the skill-match-related information and information on dissatisfaction risk factors of the employers; Talent matching methods.

[0105] A human resources matching program that causes a computer to match a plurality of workers provided by a staffing agency to a plurality of employment destinations with the plurality of employment destinations, The computer is caused to acquire aspiration-related information relating to the aspirations of the plurality of workers for the plurality of employers, skill-match-related information relating to the degree of match between the skills of the plurality of workers and the skills required by the plurality of employers, as well as information on dissatisfaction risk factors of the plurality of workers and information on dissatisfaction risk factors of the plurality of employers, and calculates, for each matching algorithm, a matching result which is a result of matching the plurality of workers with the plurality of employers based on the aspiration-related information and the skill-match-related information, and calculates a dissatisfaction index which indicates at least one of the dissatisfaction risks of the plurality of workers and the dissatisfaction risks of the plurality of employers with respect to the matching result, based on at least one of a set of information on the aspiration-related information and the dissatisfaction risk factors of the workers and a set of information on the skill-match-related information and the dissatisfaction risk factors of the employers. Talent matching program. [Explanation of symbols]

[0106] 100...terminal, 112a...skill list, 112b...appointment list, 112c...required skill list, 112d...dissatisfaction risk factor information, 160...display, 200...human resource matching device, 212a...skill match list, 212b...skill match rank table, 212c...appointment rank table, 212d...matching result, 212e...matching result with parameters, GM1...matching information input screen, GM2...matching result comparison screen

Claims

1. A human resources matching device including an information processing device that matches a plurality of workers provided by a dispatching business to a plurality of employment destinations, The information processing device includes: Acquire aspiration-related information relating to the aspirations of the plurality of workers for the plurality of workplaces, skill-match-related information relating to the degree of match between the skills of the plurality of workers and the skills required by the plurality of workplaces, as well as information on dissatisfaction risk factors of the plurality of workers and information on dissatisfaction risk factors of the plurality of workplaces; Using at least one matching algorithm based on the aspiration-related information and the skill-match-related information, calculate matching results that are results of matching between the plurality of workers and the plurality of employment opportunities for each matching algorithm; calculate a dissatisfaction index indicating at least one of a plurality of dissatisfaction risks of the workers and a plurality of dissatisfaction risks of the employers with respect to the matching results, based on at least one of a set of the aspiration-related information and information on dissatisfaction risk factors of the workers, and a set of the skill-match-related information and information on dissatisfaction risk factors of the employers; It was configured as follows: Talent matching device.

2. 2. The personnel matching device according to claim 1, The information processing device includes: A dissatisfaction risk assessment of each worker based on the aspiration-related information and information about the worker's dissatisfaction risk factors, assessing the worker's dissatisfaction risk with respect to the matching result; and a dissatisfaction risk assessment of each of the employment destinations for the matching results based on the skill match-related information and information on dissatisfaction risk factors of the employment destinations; and calculating the dissatisfaction index using the evaluation results. It was configured as follows: Talent matching device.

3. 3. The personnel matching device according to claim 2, The aspiration-related information includes aspiration information indicating the aspirations of the plurality of workers to the plurality of employment destinations, and the skill-match-related information includes skill-match information indicating the skill match between the skills of the plurality of workers and the required skills of the plurality of employment destinations, The information regarding the worker's dissatisfaction risk factors includes an accumulated dissatisfaction level of the worker, which indicates the worker's accumulated dissatisfaction with the dispatching business; The information regarding the risk factors of dissatisfaction at the workplace includes an accumulated dissatisfaction level at the workplace indicating accumulated dissatisfaction at the workplace with the dispatching business operator, The information processing device includes: A dissatisfaction risk assessment of the workers is performed by calculating a turnover risk of each of the workers in the matching results based on the aspiration level and the accumulated dissatisfaction level of the workers; A dissatisfaction risk assessment of the employment destination is performed by calculating a loss risk of each employment destination of the matching result based on the skill match degree and the accumulated dissatisfaction degree of the employment destination. It was configured as follows: Talent matching device.

4. 2. The personnel matching device according to claim 1, The aspiration-related information includes a preference ranking of each of the workers for the plurality of employment destinations, and the skill-match-related information includes a ranking of skill matches of each of the workers for the plurality of employment destinations, The information processing device includes: calculating the matching result for each matching algorithm using at least one of the matching algorithms based on the preference ranking of each worker for the plurality of employment destinations and the ranking of skill match degree of each worker for the plurality of employment destinations; It was configured as follows: Talent matching device.

5. The personnel matching device according to claim 1, The aspiration-related information includes aspiration information indicating the aspirations of the plurality of workers to the plurality of employment destinations, and the skill-match-related information includes skill-match information indicating the skill match between the skills of the plurality of workers and the required skills of the plurality of employment destinations, The information processing device includes: Using the preference information, calculate the preference ranking of each worker for the plurality of places of employment; Using the skill match information, a ranking of skill matches of each of the workers with respect to the plurality of workplaces is calculated; calculating the matching result for each matching algorithm using at least one of the matching algorithms based on the preference ranking of each worker for the plurality of employment destinations and the ranking of skill match degree of each worker for the plurality of employment destinations; It was configured as follows: Talent matching device.

6. 2. The personnel matching device according to claim 1, The information processing device includes: calculating a plurality of said matching results using a plurality of said matching algorithms; calculating the dissatisfaction index for each of the plurality of matching results; Prioritizing the plurality of matching results based on the calculated dissatisfaction index, and determining a recommended matching result from among the plurality of matching results based on the priorities. It was configured as follows: Talent matching device.

7. 2. The personnel matching device according to claim 1, The dissatisfaction index includes at least one of a turnover risk index indicating a turnover risk of the plurality of workers for the matching result, a job loss risk index indicating a job loss risk of the plurality of employers for the matching result, and a harmonic mean of the turnover risk index and the job loss risk index. Talent matching device.

8. 8. The personnel matching device according to claim 7, The aspiration-related information includes aspiration information indicating the aspirations of the plurality of workers to the plurality of employment destinations, and the skill-match-related information includes skill-match information indicating the skill match between the skills of the plurality of workers and the required skills of the plurality of employment destinations, The information on the worker's dissatisfaction risk factors includes the worker's accumulated dissatisfaction level, which indicates the worker's accumulated dissatisfaction with the dispatching business operator, and the worker's applicability, The information regarding the dissatisfaction risk factors of the workplace includes an accumulated dissatisfaction level of the workplace indicating accumulated dissatisfaction of the workplace with the dispatching business operator and an applicability of the workplace, The turnover risk index is a weighted turnover risk, The loss risk index is a weighted loss risk The information processing device includes: Calculate the turnover risk of each worker in the matching result based on the aspiration level and the accumulated dissatisfaction level of the worker, and calculate the weighted turnover risk for each worker based on the worker's applicability and the worker's turnover risk; Calculating a risk of losing each of the employment destinations in the matching results based on the skill match degree and the accumulated dissatisfaction degree of the employment destinations, and calculating the weighted risk of losing each of the employment destinations based on the applicability of the employment destinations for each of the workers and the risk of losing each of the employment destinations. It was configured as follows: Talent matching device.

9. 2. The personnel matching device according to claim 1, At least one of the matching algorithms comprises: a first matching algorithm that matches the worker with the employer so as to prioritize the skill match of the employer over the aspirations of the worker; a second matching algorithm that matches the worker with the employer so as to prioritize the aspirations of the worker over the skill match of the employer; and a third matching algorithm that matches the worker with the employer so as to strike a balance between the aspirations of the worker and the skill match of the employer. That is, Talent matching device.

10. 10. The personnel matching device according to claim 9, The information processing device Prioritizing the three matching results based on a predetermined criterion, and determining a recommended matching result from among the three matching results based on the priorities; It was configured as follows: Talent matching device.

11. 10. The personnel matching device according to claim 9, The information processing device Prioritizing the three matching results based on the harmonic mean, and determining the matching result with the lowest harmonic mean from among the three matching results as the recommended matching result based on the priorities. It was configured as follows: Talent matching device.

12. The personnel matching device according to claim 10, The system is configured to allow specification of criteria for determining the recommended matching results, The information processing device includes: Prioritizing the three matching results based on a specified criterion, and determining the recommended matching result from among the three matching results based on the priorities. It was configured as follows: Talent matching device.

13. 2. The personnel matching device according to claim 1, The information processing device includes: displaying an image showing the matching result and information about parameters related to the matching result on a display device capable of displaying the image; It was configured as follows: Talent matching device.

14. A human resources matching method using an information processing device that matches a plurality of workers provided by a dispatching business to a plurality of employment destinations, comprising: By the information processing device, Acquire aspiration-related information relating to the aspirations of the plurality of workers for the plurality of workplaces, skill-match-related information relating to the degree of match between the skills of the plurality of workers and the skills required by the plurality of workplaces, as well as information on dissatisfaction risk factors of the plurality of workers and information on dissatisfaction risk factors of the plurality of workplaces; Using at least one matching algorithm based on the aspiration-related information and the skill-match-related information, calculate matching results that are results of matching between the plurality of workers and the plurality of employment opportunities for each matching algorithm; calculate a dissatisfaction index indicating at least one of a plurality of dissatisfaction risks of the workers and a plurality of dissatisfaction risks of the employers with respect to the matching results, based on at least one of a set of the aspiration-related information and information on dissatisfaction risk factors of the workers, and a set of the skill-match-related information and information on dissatisfaction risk factors of the employers; Talent matching methods.

15. A human resources matching program that causes a computer to match a plurality of workers provided by a staffing agency to a plurality of employment destinations with the plurality of employment destinations, The computer is caused to acquire aspiration-related information relating to the aspirations of the plurality of workers for the plurality of employers, skill-match-related information relating to the degree of match between the skills of the plurality of workers and the skills required by the plurality of employers, as well as information on dissatisfaction risk factors of the plurality of workers and information on dissatisfaction risk factors of the plurality of employers, and calculates, for each matching algorithm, a matching result which is a result of matching the plurality of workers with the plurality of employers based on the aspiration-related information and the skill-match-related information, and calculates a dissatisfaction index which indicates at least one of the dissatisfaction risks of the plurality of workers and the dissatisfaction risks of the plurality of employers with respect to the matching result, based on at least one of a set of information on the aspiration-related information and the dissatisfaction risk factors of the workers and a set of information on the skill-match-related information and the dissatisfaction risk factors of the employers. Talent matching program.

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