Information providing device, method, and program

Abstract

To provide an information providing device, method, and program that make it possible to visually ascertain, for each evaluation attribute, a degree of contribution of an evaluation factor with respect to an employee's satisfaction or intention to continue.SOLUTION: An information providing device comprises: means for acquiring evaluation data about employee's satisfaction or intention to continue; multivariate analysis means for calculating a contribution degree of an explanatory variable with respect to an objective variable, using the employee's satisfaction or intention to continue as the objective variable and using a plurality of evaluation items in the evaluation data as explanatory variables; and means for causing an information terminal to display results analyzed by the multivariate analysis means. The evaluation data includes: a level 1 evaluation item corresponding to the objective variable; level 2 evaluation items that explain the objective variable; and level 3 evaluation items that explain the level 2 evaluation items. The multivariate analysis means executes: a first multivariate analysis using the evaluation values of the level 2 evaluation items as intermediate objective variables and using the level 3 evaluation items as explanatory variables; and a second multivariate analysis using the level 1 evaluation item as an objective variable and using the level 2 evaluation items as explanatory variables.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to an information providing device, method, and program for providing information that contributes to employee satisfaction or intention to continue working for an employee. [Background technology]

[0002] Conventionally, employee satisfaction surveys and awareness surveys have been conducted by conducting questionnaires on employees. For example, Patent Literature 1 discloses an evaluation device for evaluating awareness in the workplace, which is used to conduct questionnaires categorized according to the level of motivation of employees and the degree of achievement of expectations for work. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6438614 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional methods, survey results are categorized and compiled, but it is not possible to determine which factors contribute to employee satisfaction or the extent to which they contribute to employee intent to remain with the company.

[0005] An object of the present invention is to provide an information providing device, method, and program that make it possible to easily grasp the contribution of evaluation factors to an employee's satisfaction or intention to continue working for the company. [Means for solving the problem]

[0006] The inventors have invented an information providing device and program that makes it possible to easily grasp effective measures for improving employee satisfaction or intent to stay by conducting factor analysis of evaluation elements that are expected to be effective in improving employee satisfaction or intent to stay, collecting a statistically significant number of employee evaluations, and displaying the results of the statistical analysis.

[0007] An information providing device according to a first aspect of the present invention comprises: survey data acquisition means for acquiring evaluation data including evaluation values ​​of evaluation items related to employee satisfaction or intention to continue, the evaluation data including evaluation values ​​of multiple evaluation items related to employee satisfaction or intention to continue; multivariate analysis means for performing multivariate analysis using the evaluation value of employee satisfaction or intention to continue based on the evaluation data as a response variable and the evaluation values ​​of the multiple evaluation items in the evaluation data as a response variable, thereby calculating the contribution of the explanatory variables to the response variable; and analysis result output means for displaying the analysis results by the multivariate analysis means on an information terminal capable of communicating via a network, wherein the evaluation data includes level 1 evaluation items corresponding to the response variable, level 2 evaluation items explaining the response variable, and level 3 evaluation items explaining the level 2 evaluation items, and the multivariate analysis means executes a first multivariate analysis using the evaluation values ​​of the level 2 evaluation items as an intermediate response variable and the level 3 evaluation items as explanatory variables, and a second multivariate analysis using the level 1 evaluation items as response variables and the level 2 evaluation items as explanatory variables. In the above information providing device, the analysis result output means may be configured to display the plurality of explanatory variables on the information terminal using a graphic having a size corresponding to the degree of contribution. An information providing device according to a second aspect of the present invention comprises: a survey data acquisition means for acquiring evaluation data including evaluation values ​​for evaluation items related to employee satisfaction or intention to continue, the evaluation data including evaluation values ​​for multiple evaluation items related to employee satisfaction or intention to continue; a multivariate analysis means for calculating the contribution of the explanatory variables to the objective variable by performing a multivariate analysis based on the evaluation data using the evaluation value of employee satisfaction or intention to continue as an objective variable and the evaluation values ​​of the multiple evaluation items in the evaluation data as multiple explanatory variables; and an analysis result output means for displaying the analysis results by the multivariate analysis means on an information terminal capable of communicating via a network, wherein the analysis result output means displays the multiple explanatory variables on the information terminal as a figure of a size corresponding to the contribution degree. In the above information providing device, the analysis result output means may be configured to display the figures in a radial arrangement. The above-mentioned information providing device may further include a correlation analysis means for calculating an association between the plurality of explanatory variables, and the analysis result output means may be configured to display on the information terminal a line connecting pairs of the explanatory variables, the line having a thickness and / or a type corresponding to the strength of the association. The above-mentioned information providing device may further comprise a reference value setting means for setting a reference value for each of the plurality of explanatory variables, and the analysis result output means may display the explanatory variables in different colors according to their differences from the reference values. In the above information providing device, the standard value setting means may be configured to have a function of calculating an average value of the scores in the same or similar industry / business type calculated for each of the plurality of explanatory variables, and setting the average value as the standard value. In the above information providing device, the analysis result output means can be configured to color the explanatory variable in a first color when the explanatory variable is higher than the reference value, and to color the explanatory variable in a second color different from the first color when the explanatory variable is lower than the reference value.

[0008] The information provision method of the present invention is an information provision method executed by a computer to carry out the following steps: acquiring evaluation data including evaluation values ​​of evaluation items related to employee satisfaction or intention to continue, the evaluation data including evaluation values ​​of multiple evaluation items related to employee satisfaction or intention to continue; a multivariate analysis step of calculating the contribution of the explanatory variables to the objective variable by performing multivariate analysis using the evaluation values ​​of the multiple evaluation items in the evaluation data as objective variables based on the evaluation data and the evaluation values ​​of the multiple evaluation items in the evaluation data as multiple explanatory variables; and an analysis result output step of displaying the analysis results in the multivariate analysis step on an information terminal capable of communication via a network, wherein the evaluation data includes level 1 evaluation items corresponding to the objective variable, level 2 evaluation items explaining the objective variable, and level 3 evaluation items explaining the level 2 evaluation items. The program of the present invention causes a computer to execute the following: survey data acquisition means for acquiring evaluation data including evaluation values ​​for evaluation items related to employee satisfaction or intention to continue, the evaluation data including evaluation values ​​for multiple evaluation items related to employee satisfaction or intention to continue; multivariate analysis means for calculating the contribution of the explanatory variables to the objective variable by performing multivariate analysis based on the evaluation data using the evaluation value of employee satisfaction or intention to continue as an objective variable and the evaluation values ​​of the multiple evaluation items in the evaluation data as multiple explanatory variables; and analysis result output means for displaying the analysis results by the multivariate analysis means on an information terminal capable of communicating via a network, wherein the evaluation data includes level 1 evaluation items corresponding to the objective variable, level 2 evaluation items explaining the objective variable, and level 3 evaluation items explaining the level 2 evaluation items. Effect of the Invention

[0009] According to the present invention, it is possible to easily grasp the contribution of evaluation factors to an employee's satisfaction or intention to continue working. [Brief description of the drawings]

[0010] [Figure 1]1 is a configuration diagram of an information providing system according to a first embodiment. [Diagram 2] FIG. 2 is a diagram illustrating functions of the information providing device according to the first embodiment. [Diagram 3] FIG. 2 is a diagram showing an example of a survey form (summary) according to the present embodiment. [Figure 4] FIG. 4 is a diagram showing details of the questionnaire in FIG. 3. [Diagram 5] FIG. 2 is a diagram illustrating a multivariate analysis means according to the first embodiment. [Figure 6] FIG. 5 is a diagram showing the analysis results showing the contribution of each explanatory variable to employee “satisfaction” in the survey results related to the questionnaire in FIG. 4. [Figure 7] FIG. 7 is a diagram showing correlation coefficients between the explanatory variables in FIG. 6. [Figure 8] FIG. 7 is a diagram in which the contribution degree of each explanatory variable in FIG. 6 and the correlation coefficient of each explanatory variable are graphically displayed in a radial manner by the analysis result output means according to the first embodiment. [Figure 9] FIG. 13 is a diagram showing an analysis result showing the contribution of each explanatory variable to an employee's "intention to continue" according to the first embodiment. [Figure 10] FIG. 10 is a diagram in which the contribution degree of each explanatory variable in FIG. 9 and the correlation coefficient of each explanatory variable are graphically displayed in a radial manner by the analysis result output means according to the first embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] The information provision system 1 of the first embodiment allows employees to easily understand evaluation factors that affect their satisfaction or intention to continue by displaying them as numerical values ​​or graphical figures, and has the configuration described below.

[0012] Fig. 1 is a configuration diagram of an information providing system according to this embodiment. As shown in Fig. 1, the information providing system 1 according to this embodiment is composed of an information providing device 10 functioning as a server, a management information terminal 20 functioning as a management client, an information terminal 30 used by a survey respondent, a survey data collection device 40, and the Internet 50. Note that, in the example shown in Fig. 1, one each of the information providing device 10, the management information terminal 20, and the survey data collection device 40 is illustrated, but this configuration is not limited thereto, and two or more of each may be used.

[0013] The information providing device 10 is, for example, a PC server, and has a calculation unit 11, a storage unit 12 that stores an analysis program 121, and a communication unit 13 that enables communication with the information terminal 30 and the survey data collection device 40.

[0014] The management information terminal 20 is an information terminal, for example a personal computer, for inputting data into the information providing device 10 and the survey data collection device 40 and for executing the analysis program 121 and the survey data collection program 141. By executing the analysis program 121 (described later) from the management information terminal 20, the user can output various analysis results (for example, FIGS. 6 to 11) on the display device of the management information terminal 20.

[0015] The information terminal 30 is an information terminal used by the survey respondents, and is used to input survey data into the database 122. In the example of Fig. 1, the information terminal 30 is a smartphone, but is not limited to this, and can be configured as any information terminal that runs a web browser, such as a personal computer or tablet.

[0016] The survey data collection device 40 is, for example, a PC server, and has a calculation unit 41, a storage unit 42 that stores a database 122 and an input program 123, and a communication unit 13 that enables communication with the information providing device 10 and the information terminal 30. The input program 123 includes a survey data input means that provides the database 122 with a web page that enables survey data to be input from the information terminal 30. In this embodiment, the survey data is acquired by inputting the data using a web browser on the information terminal 30 via the input program 123 in the form of answering a questionnaire, but it is also possible to process survey data collected by other means, such as paper media, and upload it from the management information terminal 20 to the database 122.

[0017] 2, the calculation unit 11 of the information providing device 10 executes the analysis program 121 stored in the storage unit 12 to realize (1) a survey data acquisition means, (2) a multivariate analysis means, and (3) an analysis result output means. Each of these means will be described below.

[0018] (1) Method of collecting survey data The survey data acquisition means is a means for storing survey data to be used in the multivariate analysis means in the storage unit 12. In this embodiment, a screen for inputting a query for acquiring survey data from the database 122 is provided to the management information terminal 20. The survey data in this embodiment consists of survey data regarding employee satisfaction.

[0019] The questionnaire survey in this embodiment is a questionnaire for employees having predetermined evaluation items, and is composed of questions suitable for carrying out multivariate analysis. FIG. 3 is a diagram showing an outline of a questionnaire for the questionnaire survey of this embodiment, and FIG. 4 is a diagram showing the details of FIG. At the beginning of the questionnaire shown in FIG. 4, for example, there is an explanatory statement that the answers will not be provided to the company in a form that identifies individuals, but the questionnaire may be conducted in a form that identifies individuals. Level 1 questions consist of satisfaction and intention to continue. The former is a question asking about satisfaction with the company, and the latter is a question asking about whether you want to continue working there. Level 1 questions are the objective variables of the multiple regression analysis described below. Levels 1 to 3 questions are all multi-level evaluations. Level 2 questions are factors that affect the level 1 questions, which are the objective variables. For example, the question about contribution is a question asking about self-awareness of contributions to the company or department. Level 3 questions are explanatory variables when multiple regression analysis or correlation analysis is performed with the level 2 questions as the dependent variable. For example, the question about an excellent boss (C-2) is a question asking about whether there is a boss you would like to emulate. Here, level 2 questions and level 3 questions are in a relationship of a superordinate concept and a subordinate concept. For example, the sub-concepts of "job content" in subcategory A of level 2 questions are "clarification of goals" and "sense of accomplishment" in subcategory A of level 3 questions. However, not all subcategories of level 2 questions have level 3 questions.

[0020] In addition, an evaluation of fit may be provided as another question equivalent to the level 2 question. The question about fit may be a multi-level evaluation of a question such as, "Do you feel that this company is a good fit for you?". Note that, for the sake of convenience, the analysis results shown in Figures 6 to 10 below do not include the evaluation of fit. The sense of fit in this embodiment is a variable representing the preference structure of A, such as an individual's preference for a target, that an individual A prefers option b over option a, or that utility b is greater than utility a. By including the sense of fit that takes into account the respondent's preferences as an evaluation item, a function that enables output of the correlation between the sense of fit and clustered respondent attributes may be provided in the multivariate analysis means described below.

[0021] (2) Multivariate analysis methods The multivariate analysis means of this embodiment uses multiple regression analysis to analyze how each evaluation item affects the satisfaction and intent to continue scores (hereinafter referred to as "ES scores"). Here, regression analysis is a statistical method that clarifies the relationship between a numerical value indicating a result (objective variable) and a numerical value that is a factor (explanatory variable), and multiple regression analysis is a statistical method that quantifies the extent to which an explanatory variable influences a result when explaining an objective variable, and predicts the future. By quantifying the influence of explanatory variables using multiple regression analysis, it becomes easier to devise improvement methods. It also makes it possible to predict future changes in the objective variable that will accompany expected changes in explanatory variables.

[0022] FIG. 5 is a diagram for explaining the multivariate analysis means according to this embodiment. The multivariate analysis means of this embodiment analyzes (a) multiple regression analysis of levels 2 and 3, (b) simple correlation of level 3 evaluation factors, (c) multiple regression analysis of levels 1 and 2, and (d) simple correlation of level 2 evaluation factors. In this embodiment, by performing a hierarchical multiple regression analysis, it is possible to improve the explanatory power of the influence (contribution) of level 2 evaluation factors on employee satisfaction or intention to continue. In other words, when performing multiple regression analysis with level 3 evaluation factors as explanatory variables and evaluation values ​​of level 1 evaluation items as objective variables, it may not be possible to accurately grasp which evaluation factor is dominant, but this embodiment solves this problem by providing level 2 evaluation factors, which are intermediate concepts.

[0023] The analysis (a) is a first multiple regression analysis in which the level 2 evaluation items are the objective variables (intermediate objective variables) and the level 3 evaluation items are the explanatory variables. This analysis makes it possible to understand the level 3 evaluation items (evaluation factors) that have an effect on the level 2 evaluation items (intermediate objective variables). For example, in Figure 3, it is possible to quantify the effect (degree of contribution) of each of the clarification of goals (A-1) and the evaluation of contribution (A-2) on the evaluation of work content (A). The analysis in (b) quantifies the correlation between the evaluation factors at level 3. For example, if a simple correlation analysis reveals a high correlation between clarification of goals (A-1) and evaluation of contribution (A-2), it can be seen that an increase in the evaluation of one will also increase the evaluation of the other.

[0024] Analysis (c) is a second multiple regression analysis with the level 1 evaluation items as the objective variables and the level 2 evaluation items as the explanatory variables. This analysis makes it possible to understand the level 2 evaluation items (evaluation factors) that have an influence on the level 1 evaluation items. For example, it is possible to quantify the influence (degree of contribution) on satisfaction or intention to continue working for the company of each of the following: evaluation of work content (A), evaluation of the work environment and systems (B), evaluation of communication with those around you (C), evaluation of the company's growth potential and stability (D), evaluation of career advancement (E), and compensation (cost-effectiveness) (F) (see Figures 6 and 9). Analysis (d) calculates correlation coefficients that quantify the correlation between the evaluation factors at level 2. Figure 7 is a table showing correlation coefficients that quantify the correlation between the evaluation factors at level 2 shown in Figure 6 using simple correlation analysis. For example, Figure 7 shows a high correlation of .669 between the evaluation of job content (A) and the evaluation of career advancement (E), indicating that an increase in the evaluation of one will also increase the evaluation of the other.

[0025] Figure 6 shows an example of the results of calculating the contribution of each explanatory variable by multiple regression analysis when the objective variable is set to "satisfaction" in the survey results related to the questionnaire in Figure 4. Here, VIF (Variance Inflation Factor) is an index used to evaluate multicollinearity in multiple regression analysis. Multicollinearity means that there is a high correlation between explanatory variables, and when the VIF value is large, it is considered better to remove that variable from the analysis. Here, the coefficient of determination (R 2) is an index showing how closely the predicted value of the dependent variable obtained by multiple regression analysis matches the actual value of the dependent variable. In general, the closer the coefficient of determination is to 1, the higher the explanatory power. In the example shown in Figure 6, it can be seen that "job content" has the highest contribution to satisfaction, followed by "company growth potential and stability." Figure 6 also shows that the VIFs of each explanatory variable are not large, indicating that no problems with multicollinearity have occurred. Figure 6 also shows that the coefficient of determination, R 2 is large at .703, indicating that this is an analysis with high explanatory power.

[0026] In addition, the multivariate analysis means according to this embodiment also has a function of calculating the evaluation difference from a comparative score (for example, the average score of each evaluation item in an employee satisfaction survey in the same or similar industry or business type; hereinafter referred to as a "standard score"). As shown in Fig. 6, by looking at the evaluation difference from the standard score calculated for each explanatory variable, it is possible to grasp the strengths and weaknesses of one's company compared to other companies.

[0027] (3) Analysis result output means The analysis result output means of this embodiment not only outputs the analysis results in a table format as shown in Figs. 6 to 7 and 9, but also graphically displays the contribution of explanatory variables to the objective variable (ES score), allowing visual understanding (see Figs. 8 and 10). In this embodiment, each explanatory variable is graphically displayed as a circle of a size proportional to the contribution to the ES score. Also, in this embodiment, when the contribution is below a certain level, the circle is drawn with a predetermined minimum radius, and is not made to be smaller than the minimum radius. Note that the size of the circle does not necessarily have to be proportional to the contribution value, and it may be highlighted (for example, the top two explanatory variables may be displayed large by multiplying the contribution value by a coefficient).

[0028] The analysis result output means has a function of coloring explanatory variables with a higher rating than the standard rating in a first color, and explanatory variables with a lower rating than the standard rating in a second color. In this embodiment, the average score of the respondents' evaluation values ​​is calculated for each explanatory variable, and explanatory variables with an average rating higher than the standard rating are colored green (diagonal lines), and explanatory variables with an average rating lower than the standard rating are colored red (dots). Here, in this embodiment, the greater the difference between the average rating of the explanatory variables and the standard rating, the darker the color is drawn.

[0029] In addition, in this embodiment, explanatory variables having a specific correlation coefficient are connected and displayed by a correlation display line. Any rule can be set for the display method of the correlation display line, and for example, the top few pairs that are 0.4 or more after rounding off the least significant digit may be displayed. In addition, the correlation display line of this embodiment adopts a rule that a value that is 0.7 or more after rounding off the least significant digit is displayed as a double line, a value less than 0.7 to 0.6 or more is displayed as a thick solid line, a value less than 0.6 to 0.5 or more is displayed as a solid line of normal thickness, a value less than 0.5 to 0.4 or more is displayed as a thin dotted line, and a value less than 0.4 is not displayed.

[0030] FIG. 8 is a diagram in which the contribution of each explanatory variable and the correlation coefficient of each explanatory variable are graphically displayed by the analysis result output means when the objective variable shown in FIG. 6 is set to satisfaction. In FIG. 8, the diagonal lines indicate the first color, green, and the dots indicate the second color, red. In FIG. 8, "Remuneration (Cost Performance)" and "Work Environment and Systems" are colored red, so it can be seen at a glance that the average score is particularly lower than the standard score.

[0031] In addition, in FIG. 8, each explanatory variable is drawn by a circle whose size corresponds to the numerical value of its contribution to satisfaction. From the size of the circle in FIG. 8, it can be seen that "job content" has the strongest influence on satisfaction, followed by "growth potential and stability of the company". In this embodiment, the circles corresponding to each explanatory variable are arranged at the vertices of a regular hexagon, but the drawing method is not limited to this, and the explanatory variables may be arranged at the vertices of any regular polygon according to the number of explanatory variables, or may be arranged at equal intervals on the circumference. In addition, the arrangement order of the figures representing the explanatory variables may be changed by a drag operation.

[0032] In addition, in Figure 8, the thickness and type of the correlation lines connecting the explanatory variables make it possible to visually grasp the correlation between the explanatory variables. For example, it can be seen that "career advancement" has a strong influence on "job content", which is connected by a solid correlation line. In this way, by graphically displaying the correlation coefficients of each explanatory variable with correlation lines of different thicknesses and types, it is possible to easily grasp the factors that affect employee satisfaction. Note that the number of explanatory variables connected by the correlation lines is not limited to the number shown in the example, and any number of correlation lines can be displayed.

[0033] In this embodiment, the explanatory variables are represented by circles whose size is proportional to the degree of contribution, but the figure showing the degree of contribution is not limited to this and any figure can be used, for example, a polygon or an illustration of food or a character. The arrangement order of the figures showing the explanatory variables may be changed by a drag operation. A function may be added to arrange the explanatory variables in ascending or descending order according to the degree of contribution, or in ascending or descending order according to the score.

[0034] Figure 9 shows the analysis results showing the contribution of each explanatory variable (evaluation factor) at level 2 when the objective variable is set to "intention to continue." In the example shown in Figure 9, it can be seen that "job content" has the highest contribution to the intention to continue, followed by "career advancement." In addition, the VIF of each explanatory variable is not a large value, which shows that no problem of multicollinearity has occurred. Also, in Figure 9, the coefficient of determination R 2 Since the mean score is .668, it can be seen that this analysis has a high explanatory power. Furthermore, in Figure 9, similar to Figure 6, the evaluation difference from the standard score for each explanatory variable is also calculated.

[0035] Fig. 10 is a diagram in which the contribution of each explanatory variable in Fig. 9 and the correlation coefficient of each explanatory variable are graphically displayed radially by the analysis result output means. In Fig. 10, the diagonal lines indicate the first color, green, and the dots indicate the second color, red. In Figure 10, only "Remuneration (cost-effectiveness)" and "Work environment and system" are colored red, so you can immediately see that these are the only ones that are rated lower than the standard score (for example, the average value in the same industry or in a different field). Also, since the intent to continue, job content, career advancement, and communication with others are colored darker, you can see that they are rated significantly higher than the standard score. Also, like in Figure 8, two explanatory variables are connected by a correlation line whose thickness and type correspond to the value of the correlation coefficient.

[0036] As described above, according to the information provision system 1 of this embodiment, the analysis results obtained by multivariate analysis of dependent variables and explanatory variables (evaluation factors) are graphically visualized and provided, making it possible to instantly grasp the dependent variables for efficiently carrying out improvement efforts. In addition, by providing a graphical visualization of explanatory variables with high correlation coefficients, it becomes possible to easily predict the impact of improving the explanatory variables.

[0037] Although the preferred embodiment of the present invention has been described above, the technical scope of the present invention is not limited to the description of the above embodiment. Various modifications and improvements can be made to the above embodiment, and such modifications and improvements are also included in the technical scope of the present invention.

[0038] For example, in the above-described embodiment, a configuration was exemplified in which multiple regression analysis, a type of multivariate analysis, was used to determine the contribution of each evaluation factor to the ES score, but this configuration is not limited to this, and principal component analysis, factor analysis, correspondence analysis, multidimensional scaling, cluster analysis, path analysis, analysis of variance, conjoint analysis, regression analysis, logistics regression analysis, etc. may also be used. In addition to the above-described embodiment, the information providing device 10 can also be configured to collect condition information such as respondent attributes and workplace, and to analyze the evaluation factors that contribute to the ES score by taking into account the condition information. Also, by adding graphic attributes and psychographic attributes to the questionnaire, analysis by respondent attributes is possible.

[0039] In the above-described embodiment, an example was described in which a hierarchical multiple regression analysis was performed to enhance the explanatory power of the influence (contribution) of evaluation factors on the ES score. However, the technical concept of the present invention is also applicable to multivariate analysis using non-hierarchical evaluation factors. [Explanation of symbols]

[0040] 1. Information provision system 10...Information provision device 20...Administrative information terminal 30…Information terminal 40...Survey data collection device 50…Internet

Claims

1. A survey data acquisition means for acquiring evaluation data including evaluation values ​​of evaluation items related to employee satisfaction or intent to continue, the evaluation data including evaluation values ​​of a plurality of evaluation items related to employee satisfaction or intent to continue; a multivariate analysis means for performing a multivariate analysis using an evaluation value of employee satisfaction or intent to continue based on the evaluation data as a response variable and evaluation values ​​of a plurality of evaluation items in the evaluation data as a plurality of explanatory variables to calculate a contribution of the explanatory variables to the response variable; and an analysis result output means for displaying the analysis result by the multivariate analysis means on an information terminal capable of communicating via a network, the evaluation data includes level 1 evaluation items corresponding to the objective variable, level 2 evaluation items explaining the objective variable, and level 3 evaluation items explaining the level 2 evaluation items, The information providing device is characterized in that the multivariate analysis means executes a first multivariate analysis in which the evaluation values ​​of the level 2 evaluation items are used as intermediate objective variables and the level 3 evaluation items are used as explanatory variables, and a second multivariate analysis in which the level 1 evaluation items are used as objective variables and the level 2 evaluation items are used as explanatory variables.

2. A survey data acquisition means for acquiring evaluation data including evaluation values ​​of evaluation items related to employee satisfaction or intent to continue, the evaluation data including evaluation values ​​of a plurality of evaluation items related to employee satisfaction or intent to continue; a multivariate analysis means for performing a multivariate analysis using an evaluation value of employee satisfaction or intent to continue based on the evaluation data as a response variable and evaluation values ​​of a plurality of evaluation items in the evaluation data as a plurality of explanatory variables to calculate a contribution of the explanatory variables to the response variable; and an analysis result output means for displaying the analysis result by the multivariate analysis means on an information terminal capable of communicating via a network, The information providing device is characterized in that the analysis result output means displays the plurality of explanatory variables on the information terminal in the form of a graphic having a size corresponding to the degree of contribution.

3. 2. The information providing device according to claim 1, wherein said analysis result output means causes said plurality of explanatory variables to be displayed on said information terminal in the form of a graphic having a size corresponding to said contribution degree.

4. 4. The information providing device according to claim 2, wherein the analysis result output means displays the figures in a radial arrangement.

5. Further, a correlation analysis means for calculating a correlation between the plurality of explanatory variables is provided, The information providing device according to claim 2 or 3, characterized in that the analysis result output means displays on the information terminal a line connecting pairs of explanatory variables, the line having a thickness and / or a type corresponding to the strength of the association.

6. Further, a reference value setting means for setting a reference value for each of the plurality of explanatory variables is provided, 4. The information providing apparatus according to claim 2, wherein the analysis result output means displays the explanatory variables in different colors according to the differences from the reference values.

7. The information providing device according to claim 6, characterized in that the standard value setting means has a function of calculating an average value of the scores calculated for each of the multiple explanatory variables in the same or similar industry or business type, and setting the average value as the standard value.

8. 7. The information providing device according to claim 6, characterized in that the analysis result output means colors the explanatory variable in a first color when the explanatory variable has a value higher than the reference value, and colors the explanatory variable in a second color different from the first color when the explanatory variable has a value lower than the reference value.

9. acquiring evaluation data including evaluation values ​​of evaluation items related to employee satisfaction or intent to continue, the evaluation data including evaluation values ​​of a plurality of evaluation items related to employee satisfaction or intent to continue; a multivariate analysis step of calculating the contribution of each explanatory variable to the objective variable by performing a multivariate analysis using an evaluation value of employee satisfaction or intention to continue working based on the evaluation data and an evaluation value of each of a plurality of evaluation items in the evaluation data as a plurality of explanatory variables; An information providing method, comprising: an analysis result output step of displaying the analysis result in the multivariate analysis step on an information terminal capable of communicating via a network, the information providing method being executed by a computer, the evaluation data includes level 1 evaluation items corresponding to the objective variable, level 2 evaluation items explaining the objective variable, and level 3 evaluation items explaining the level 2 evaluation items, This information provision method is characterized in that in the multivariate analysis step, a first multivariate analysis is performed in which the evaluation values ​​of the level 2 evaluation items are used as intermediate objective variables and the level 3 evaluation items are used as explanatory variables, and a second multivariate analysis is performed in which the level 1 evaluation items are used as objective variables and the level 2 evaluation items are used as explanatory variables.

10. a survey data acquisition means for acquiring evaluation data including evaluation values ​​of evaluation items related to employee satisfaction or intent to continue working, the evaluation data including evaluation values ​​of a plurality of evaluation items related to employee satisfaction or intent to continue working, in a computer; a multivariate analysis means for performing a multivariate analysis using an evaluation value of employee satisfaction or intent to continue based on the evaluation data as a response variable and evaluation values ​​of a plurality of evaluation items in the evaluation data as a plurality of explanatory variables to calculate a contribution of the explanatory variables to the response variable; and an analysis result output means for displaying the analysis result by the multivariate analysis means on an information terminal capable of communicating via a network, the evaluation data includes level 1 evaluation items corresponding to the objective variable, level 2 evaluation items explaining the objective variable, and level 3 evaluation items explaining the level 2 evaluation items, The program is characterized in that the multivariate analysis means executes a first multivariate analysis in which the evaluation values ​​of the level 2 evaluation items are intermediate objective variables and the level 3 evaluation items are explanatory variables, and a second multivariate analysis in which the level 1 evaluation items are objective variables and the level 2 evaluation items are explanatory variables.

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