CN102646229A - Fuzzy comprehensive evaluation method of adaptation between employee and position of enterprise - Google Patents
Fuzzy comprehensive evaluation method of adaptation between employee and position of enterprise Download PDFInfo
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Abstract
The invention relates to a fuzzy comprehensive evaluation method of adaptation between an employee and a position of an enterprise. The method comprises the following steps of: step 1: selecting a position adaptation subjective evaluation method; step 2: establishing a position adaptation evaluation factor set; step 3: establishing a position adaptation evaluation comment set; step 4: determining a fuzzy relation from the evaluation factor set to the evaluation comment set; step 5: establishing a weight set of position adaptation evaluation factors; and step 6: establishing a position adaptation fuzzy comprehensive evaluation model. The method disclosed by the invention has the technical effects that: the adaptation degree between the employee and the position can be rapidly quantified based on the position adaptation fuzzy comprehensive evaluation model according to the established position adaptation evaluation system, the theoretical blank in the field of position adaptation evaluation of the enterprise is filled up, all-level managers of the enterprise can be guided to perform employee position configuration in an objective, accurate and reasonable manner, and the method can play a positive impelling role in upgrading the core competitiveness of the enterprise.
Description
Technical field
The present invention relates to the talent evaluation technology, relate in particular to a kind of adaptive fuzzy comprehensive evaluation method of enterprise staff and post that is applicable to.
Background technology
Market competition makes enterprise face increasing challenge, and the core competitiveness of self must improve to obtain the advantage of sustainable development in enterprise.And the lifting of core competitiveness is that the employee satisfies the lifting that working requires ability on the one hand after all, on the other hand the employee is put into suitable post to promote the maximization performance of its ability.But company managers have spent a lot of time and efforts to customize more complete management system and distinct post setting, but next but find in employee's selection, to have run into difficulty.The challenge that at first runs into is exactly a ability quality how to accomplish objectively and impartially to estimate leader and employees.Secondly, be exactly how can more accurately the employee be placed on the suitable post.Therefore, correctly estimate the adaptive degree in employee and post, increasingly important for the development of enterprise.
Yet, because the otherness of different employee's ability qualities and the singularity of different post capability quality demands even make to have the century-old enterprise that enriches managerial experience, still also do not form the appraisement system whether mate in employee and post up to now.The all levels of management personnel of enterprise estimate through subjectivity, fuzzy speech the judge whether employee is fit to the post; Be difficult to quantize with Exact Number; Thereby influenced the accuracy of estimating, weakened the rationality of employee and post coupling, influenced giving full play to of employee's ability.
Summary of the invention
In order to quantize the evaluation of employee post fit; The present invention provides a kind of employee post fit comprehensive evaluation method based on step analysis; Create appraisement system, in the hope of guiding company manager correct carry out employee's post setting, improve employee and post matched accuracy and rationality.
For realizing above-mentioned purpose, the present invention realizes like this.The present invention is a kind of enterprise staff post fit comprehensive evaluation method based on step analysis, and concrete steps are:
Step 1: select the adaptive subjective evaluation method in post
Select fuzzy comprehensive evaluation method for use: adopt the fuzzy mathematics adaptive evaluation in multifactorial evaluation post;
Fuzzy mathematics is the mathematical method of the fuzzy uncertain problem of research; By the standard of confirming, certain factor or certain part in certain or certain class object are estimated, be called single judge: from numerous single judges, obtain the overall evaluation, be called multifactorial evaluation to certain or certain class object; The purpose of multifactorial evaluation is normally hoped and can some objects be sorted by certain meaning, selects optimum and the most bad object; Therefore, fuzzy comprehensive evoluation is the good approach that the post fit is estimated;
Multifactorial evaluation function commonly used has weighted mean type, geometric mean type, single factor decision type and main factor protruding type.Because of the adaptive effect in post is decided by many-sided combined factors, what the present invention adopted is the multifactorial evaluation function of weighted mean type:
Step 2: set up the adaptive evaluation factor collection in post
Through the data investigation with to enterprise administrator, staff manager, professional and technical personnel, technical ability personnel, support personnel's interview, set up post adaptive evaluation factor collection U={u
1, u
2..., u
n), u wherein
1～u
nBe evaluation factor;
Step 3: set up post adaptive judge comment collection
Different posies is under different responsibility demands; The adaptive degree in its post requires different, therefore sets up the judge comment collection of being made up of the adaptive degree in post, and adopts expert's point system to the adaptive opinion rating marking in each post; Obtain the value of opinion rating, pass judgment on comment collection V={v
1, v
2..., v
n, v wherein
1～v
nFor passing judgment on comment;
Step 4: confirm from the evaluation factor collection to the fuzzy relation of passing judgment on the comment collection
Set up under the different job duty demands from the post adaptive evaluation factor collection U to the fuzzy relation matrix of passing judgment on comment collection V; At first confirm each the evaluation factor u among the evaluation factor collection U
iTo passing judgment on comment v
jDegree of membership r
Ij, i=1 wherein, 2 ..., n, j=1,2 ..., m; Each evaluation factor u
iJudge comment collection be r
Ij={ r
I1, r
I2..., r
In; The judge comment collection of all evaluation factors is constituted the evaluation matrix R on m * n rank, that is:
Step 5: the weight sets of setting up the adaptive evaluation factor in post
Confirm weight sets according to expert's evaluation method of judging (Delphi method).Expert's evaluation method of judging has certain subjectivity and randomness; For the objectivity and the correctness of appraising the result through discussion, need subjective weight be modified to objective weight, because information entropy is probabilistic tolerance; Degree of variation according to each evaluation factor; Utilize the subjective weight of information entropy correction, thereby obtain the multifactorial evaluation weight, the weight sets that evaluation factor U is corresponding is W=(w
1, w
2..., w
m);
Step 6: set up the adaptive fuzzy synthetic evaluation model in post, carry out multifactorial evaluation
Adopt weighted mean type multifactorial evaluation function, can obtain the adaptive fuzzy synthetic evaluation model in post and be:
Wherein, ο is the product sum operation, passes judgment on matrix A for passing judgment on the fuzzy subset on the comment collection V, is the result vector of the adaptive fuzzy comprehensive evoluation in post:
Based on passing judgment on matrix A and passing judgment on the value of passing judgment on comment among the comment collection V, obtaining final evaluation result is B:
B＝A·V
T
Evaluation result B is compared with passing judgment on the value of passing judgment on comment among the comment collection V, draw the adaptive degree in post.
The technical characterstic of the inventive method is:
The present invention is based on the post adaptation method of fuzzy comprehensive evoluation; Be different from non-quantization method artificial subjective judgement traditional, the doping emotional factor, the fuzzy evaluation language, proposed the complete effective adaptive quantitative evaluation system of enterprise staff and post that is applicable to of a cover.
The technique effect of the inventive method is:
Utilize the method; Can be based on the adaptive fuzzy synthetic evaluation model in post; According to the adaptive appraisement system of creating in post; Quantize the fit in employee and post rapidly, filled up adaptive evaluation field, enterprise post theory blank, effective appraisement system and method; Can guide the supvrs at different levels of enterprise objective, accurate, reasonably carry out employee post configuration, to promoting the employee to give full play to self ability level and clever material in suitable post, strengthen the scientific human resource management of enterprise, promoting enterprise core competence and played positive prograding.
Description of drawings
Fig. 1 is a kind of process flow diagram that is applicable to the fuzzy comprehensive evaluation method that enterprise staff and post are adaptive of the present invention.
The practical implementation method
Below in conjunction with specific embodiment, further set forth the present invention.Should be understood that embodiment only to be used to the present invention is described and be not used in the restriction scope of the present invention.Should be understood that in addition those skilled in the art can make various changes or modification to the present invention after the content of reading the present invention's instruction, these equivalent form of values fall within the application's appended claims institute restricted portion equally.
Embodiment 1: the adaptive fuzzy comprehensive evoluation in employee post, electric power enterprise safety monitor post
Step 1: select the adaptive subjective evaluation method in post
The adaptive degree in post is embodied in different aspects; As strict and meticulous, safety supervision etc. are different in the ratio of each factor in judge; And; Managerial personnel are the vague descriptions of non-quantitation to the evaluation language of post fit each side traditionally, and these all make the evaluation personnel be difficult to the post fit is made multifactorial evaluation, thereby have influenced the correctness of estimating.
Fuzzy mathematics is the mathematical method of the fuzzy uncertain problem of research.By the standard of confirming, certain factor or certain part in certain or certain class object are estimated, be called single judge.From numerous single judges, obtain the overall evaluation, be called multifactorial evaluation certain or certain class object.The purpose of multifactorial evaluation is normally hoped and can some objects be sorted by certain meaning, selects optimum and the most bad object.Therefore, fuzzy comprehensive evoluation is the good approach that the post fit is estimated.
Multifactorial evaluation function commonly used has weighted mean type, geometric mean type, single factor decision type and main factor protruding type.Because of the adaptive effect in post is decided by many-sided combined factors, what the present invention adopted is the multifactorial evaluation function of weighted mean type.
Step 2: set up the adaptive evaluation factor collection in post
Through the data investigation with to enterprise administrator, staff manager, professional and technical personnel, technical ability personnel, support personnel's interview.Simultaneously; The performance standard requirement concrete according to the post, in the employee who is engaged in the work of safety monitor post, the employee who from the employee of high performance and common performance, randomly draws some respectively analyzes and researches; Obtain the characteristic of the relevant quality of sample; Set up post adaptive evaluation factor collection U, wherein
U={ plans to advance, safety monitor, accident event is handled, statistical study };
Step 3: set up post adaptive judge comment collection
The ambiguity adaptive according to the post will be passed judgment on the comment collection and be divided into four excellent a of opinion rating: V={, good b, middle c, difference d}.Adopt expert's point system to the adaptive opinion rating marking in each post, obtain the value of opinion rating, be V={ difference d, middle c, good b, excellent a}={0.1,0.4,0.6,0.8};
Step 4: confirm from the evaluation factor collection to the fuzzy relation of passing judgment on the comment collection
Set up under the different job duty demands from the post adaptive evaluation factor collection U to the fuzzy relation matrix of passing judgment on comment collection V; At first confirm each the evaluation factor u among the evaluation factor collection U
iTo passing judgment on comment v
jDegree of membership r
Ij, i=1 wherein, 2 ..., n, j=1,2 ..., m: each evaluation factor u
iJudge comment collection be r
Ij={ r
I1, r
I2..., r
In}: the judge comment collection of all evaluation factors is constituted the evaluation matrix R on m * n rank, that is:
Step 5: the weight sets of setting up the adaptive evaluation factor in post
Confirm weight sets according to expert's evaluation method of judging (Delphi method).Expert's evaluation method of judging has certain subjectivity and randomness, for the objectivity and the correctness of appraising the result through discussion, need subjective weight be modified to objective weight.Because information entropy is probabilistic tolerance,, utilizes the subjective weight of information entropy correction, thereby obtain the multifactorial evaluation weight according to the degree of variation of each evaluation factor.The weight sets that evaluation factor U is corresponding is W=(plan advances, safety monitor, accident event processing, statistical study)=(0.296,0.296,0.037,0.038);
Step 6: set up the adaptive fuzzy synthetic evaluation model in post, carry out multifactorial evaluation
Adopt weighted mean type multifactorial evaluation function, can obtain the adaptive fuzzy synthetic evaluation model in post and be:
Wherein, ο is the product sum operation, passes judgment on matrix A for passing judgment on the fuzzy subset on the comment collection V, is the result vector of the adaptive fuzzy comprehensive evoluation in post:
Based on passing judgment on matrix A and passing judgment on the value of passing judgment on comment among the comment collection V, obtaining final evaluation result is B, wherein,
B＝A·V
T＝(0.1952，0.2739，0.2341，0.2092)·(0.1，0.4，0.6，0.8)
T＝0.4369
With evaluation result B with to pass judgment on comment collection V={ poor, in, good, excellent={ 0.1,0.4,0.6, the value of passing judgment on comment among the 0.8} compares, and the adaptive degree B in post is between neutralization very, and the adaptive degree in this post is good.
Embodiment 2: the adaptive fuzzy comprehensive evoluation in electric power enterprise cable fortune inspection employee post, post
Step 1: select the adaptive subjective evaluation method in post
The adaptive degree in post is embodied in different aspects; As strict and meticulous, safety supervision etc. are different in the ratio of each factor in judge; And; Managerial personnel are the vague descriptions of non-quantitation to the evaluation language of post fit each side traditionally, and these all make the evaluation personnel be difficult to the post fit is made multifactorial evaluation, thereby have influenced the correctness of estimating.
Fuzzy mathematics is the mathematical method of the fuzzy uncertain problem of research.By the standard of confirming, certain factor or certain part in certain or certain class object are estimated, be called single judge, from numerous single judges, obtain the overall evaluation to certain or certain class object, be called multifactorial evaluation.The purpose of multifactorial evaluation is normally hoped and can some objects be sorted by certain meaning, selects optimum and the most bad object.Therefore, fuzzy comprehensive evoluation is the good approach that the post fit is estimated.
Multifactorial evaluation function commonly used has weighted mean type, geometric mean type, single factor decision type and main factor protruding type.Because of the adaptive effect in post is decided by many-sided combined factors, what the present invention adopted is the multifactorial evaluation function of weighted mean type.
Step 2: set up the adaptive evaluation factor collection in post
Through the data investigation with to enterprise administrator, staff manager, professional and technical personnel, technical ability personnel, support personnel's interview.Simultaneously; The performance standard requirement concrete according to the post, in the employee who is engaged in cable fortune inspection post work, the employee who from the employee of high performance and common performance, randomly draws some respectively analyzes and researches; Obtain the characteristic of the relevant quality of sample; Set up post adaptive evaluation factor collection U, wherein
U={ plans to advance, the inspection of cable fortune, accident event is handled, statistical study };
Step 3: set up post adaptive judge comment collection
The ambiguity adaptive according to the post will be passed judgment on the comment collection and be divided into four excellent a of opinion rating: V={, good b, middle c, difference d}: adopt expert's point system to the adaptive opinion rating marking in each post; Obtain the value of opinion rating, be V={ difference d, middle c, good b; Excellent a}={0.1,0.4,0.6,0.8};
Step 4: confirm from the evaluation factor collection to the fuzzy relation of passing judgment on the comment collection
Set up under the different job duty demands from the post adaptive evaluation factor collection U to the fuzzy relation matrix of passing judgment on comment collection V; At first confirm each the evaluation factor u among the evaluation factor collection U
iTo passing judgment on comment v
jDegree of membership r
Ij, i=1 wherein, 2 ..., n, j=1,2 ..., m; Each evaluation factor u
iJudge comment collection be r
Ij={ r
I1, r
I2..., r
In; The judge comment collection of all evaluation factors is constituted the evaluation matrix R on m * n rank, that is:
Step 5: the weight sets of setting up the adaptive evaluation factor in post
Confirm weight sets according to expert's evaluation method of judging (Delphi method).Expert's evaluation method of judging has certain subjectivity and randomness, for the objectivity and the correctness of appraising the result through discussion, need subjective weight be modified to objective weight.Because information entropy is probabilistic tolerance,, utilizes the subjective weight of information entropy correction, thereby obtain the multifactorial evaluation weight according to the degree of variation of each evaluation factor.The weight sets that evaluation factor U is corresponding is W=(plan advances, and cable fortune is examined, and accident event is handled, statistical study)=(0.296,0.296,0.037,0.038);
Step 6: set up the adaptive fuzzy synthetic evaluation model in post, carry out multifactorial evaluation
Adopt weighted mean type multifactorial evaluation function, can obtain the adaptive fuzzy synthetic evaluation model in post and be:
Wherein, ο is the product sum operation, passes judgment on matrix A for passing judgment on the fuzzy subset on the comment collection V, is the result vector of the adaptive fuzzy comprehensive evoluation in post;
Based on passing judgment on matrix A and passing judgment on the value of passing judgment on comment among the comment collection V, obtaining final evaluation result is B, wherein,
B＝A·V
T＝(0.3293，0.2426，0.1894，0.1630)·(0.1，0.4，0.6，0.8)
T＝0.3740
With evaluation result B with to pass judgment on comment collection V={ poor, in, good, excellent=0.1,0.4,0.6, the value of passing judgment on comment among the 0.8} compares, and the adaptive degree B in post between difference and between, the adaptive degree in this post is poor.
Claims (1)
1. the adaptive fuzzy comprehensive evaluation method of enterprise staff and post is characterized in that, comprises following step:
Step 1: select the adaptive subjective evaluation method in post
Select fuzzy comprehensive evaluation method for use: adopt the fuzzy mathematics adaptive evaluation in multifactorial evaluation post;
Step 2: set up the adaptive evaluation factor collection in post
Through the data investigation with to enterprise administrator, staff manager, professional and technical personnel, technical ability personnel, support personnel's interview, set up post adaptive evaluation factor collection U={u
1, u
2..., u
n, u wherein
1～u
nBe evaluation factor;
Step 3: set up post adaptive judge comment collection
Different posies is under different responsibility demands; The adaptive degree in its post requires different, therefore sets up the judge comment collection of being made up of the adaptive degree in post, and adopts expert's point system to the adaptive opinion rating marking in each post; Obtain the value of opinion rating, pass judgment on comment collection V={v
1, v
2..., v
n, v wherein
1～v
nFor passing judgment on comment;
Step 4: confirm from the evaluation factor collection to the fuzzy relation of passing judgment on the comment collection
Set up under the different job duty demands from the post adaptive evaluation factor collection U to the fuzzy relation matrix of passing judgment on comment collection V; At first confirm each the evaluation factor u among the evaluation factor collection U
iTo passing judgment on comment v
jDegree of membership r
Ij, i=1 wherein, 2 ..., n, j=1,2 ..., m; Each evaluation factor u
iJudge comment collection be r
Ij={ r
I1, r
I2..., r
In; The judge comment collection of all evaluation factors is constituted the evaluation matrix R on m * n rank, that is:
Step 5: the weight sets of setting up the adaptive evaluation factor in post
Confirm weight sets according to expert's evaluation method of judging (Delphi method), expert's evaluation method of judging has certain subjectivity and randomness, for the objectivity and the correctness of appraising the result through discussion; Need subjective weight be modified to objective weight; Because information entropy is probabilistic tolerance,, utilize the subjective weight of information entropy correction according to the degree of variation of each evaluation factor; Thereby obtain the multifactorial evaluation weight, the weight sets that evaluation factor U is corresponding is W=(w
1, w
2..., w
m);
Step 6: set up the adaptive fuzzy synthetic evaluation model in post, carry out multifactorial evaluation
Adopt weighted mean type multifactorial evaluation function, can obtain the adaptive fuzzy synthetic evaluation model in post and be:
Wherein, " ο " is the product sum operation, passes judgment on matrix A for passing judgment on the fuzzy subset on the comment collection V, is the result vector of the adaptive fuzzy comprehensive evoluation in post;
According to passing judgment on matrix A and passing judgment on the value of passing judgment on comment among the comment collection V, obtaining final evaluation result is B, wherein B=AV
T, evaluation result B is compared with passing judgment on the value of passing judgment on comment among the comment collection V, draw the adaptive degree in post.
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Application publication date: 20120822 |