Comprehensive Evaluation on Employee Satisfaction of Mine Occupational Health and Safety Management System Based on FAHP and 2T uple Linguistic Information

In order to comprehensively evaluate the employee satisfaction of mine occupational health and safety management system, an analytic method based on fuzzy analytic hierarchy process and 2tuple linguistic model was established. Firstly, based on the establishment of 5 firstgrade indicators and 20 secondgrade ones, the weight of each indicator is calculated and validated by method of FAHP and root mean square model. Secondly, a path based on the time-ordered Weighted Averaging Operator (T-OWA) model is constructed. Finally, the model is validated by empirical analysis. The results demonstrate that the employee satisfaction of the mine occupational health and safety management system is of the “general” rank. The method including the comprehensive evaluation of employee satisfaction and the quantitative analysis of language evaluation information ensures the authenticity of the language evaluation information.


Introduction
To a large extent, employee satisfaction not only determines the survival and development of enterprises, but also the core idea of quality, environment, occupational health and safety management system.Scientific and effective evaluation of enterprise employee satisfaction is not only the requirement of the enterprise strategy development, but also has an important reference value for the continuous improvement of the enterprise.At present, the research on employee satisfaction mainly focuses on its composition, influencing factors and evaluation system.The evaluation method [1] concentrates upon the balance integral card, structural equation model, grey system model, fuzzy analytic hierarchy process, principal component analysis, factor analysis, logistic regression analysis and so on, however, the evaluation of employee satisfaction is a kind of subjective value judgment, which is fuzzy and uncertain.In the evaluation, it is usually difficult for the participants to accurately determine the satisfaction with precise numbers or language, the acquired language information is usually not directly involved in mathematical operations, resulting in loss of information and accuracy [2].
Herrera [3] put forward 2-tuple linguistic information and the corresponding aggregation operator for the first time, which can solve the defects of the above methods, and can ensure the integrity and authenticity of the information in the process of language information gathering and processing.Therefore, this paper applies 2-tuple linguistic information processing method to the evaluation of employee satisfaction, combined with FAHP model to ensure the reliability of the indicator weight.Also, the specific evaluation steps and calculation process are given, and the feasibility and effectiveness of the method is verified by a case.

Mine Occupational Health and safety management system employee satisfaction indicators
In full consideration of the basis of employee satisfaction evaluation indicators given by domestic and foreign scholars [4][5][6][7][8][9][10][11], combined with the OHSAS18001 standard requirements [12], employee satisfaction evaluation first and second-grade indicators of the OHSAS18001 are given as is shown in Table 1.

Humanization of OHSAS
Humanization of OHSAS is to meet the needs of people's all-round development.Implementation of the project is bound to affect the people, mainly in the following aspects: training opportunities, promotion opportunities, Information openness and access to development opportunities.

Effectiveness of OHSAS
Effectiveness is the activity of planning and the degree to which the planning results are achieved.According to the requirements of OHSAS, Effectiveness is mainly manifested in the following aspects: continuous improvement, communication, coordination and cooperation of work and effectiveness of management.

Economical efficiency of OHSAS
Economical efficiency is an economic activity that can be consumed by the least active labor and physical labor, and the ability to achieve the greatest economic results, which is mainly manifested in the following aspects: pay level, welfare, operating performance and economic structure.

.Social efficiency of OHSAS
Social efficiency is a living creature as a collective activity, or as a member of society with characteristics which is beneficial to the collective and social development which is mainly manifested in the following aspects: related party, community, customs of the people's life and social culture.

Environmental efficiency of OHSAS
Environmental efficiency is a kind of adaptation to nature and activities of protecting the nature which is mainly manifested in the following aspects: natural resource consumption, comprehensive utilization of natural resources, ecological management cost and environmental sustainable development.

Evaluation weight set
In this paper, the importance among indicators is scored by the relevant experts, to determine the weight value of each indicator in this factor and to construct the judgment matrix referring to 1 ~ 9 scale method proposed by A L Saaty to determine the specific values.If the parameter on the horizontal axis was less important than the parameter on the vertical axis, it carried a value between 1 and 9. Oppositely, it carried the value between the reciprocals of 1/2 and 1/9 [13].

Consistency checking
The test index for the consistency of judgment is as follows ：CR = CI/RI; In the equation，CI= (λ-n)/(n -1), n is the order of the judgment matrix.RI is random consistency index of judgment matrix [14].Suppose the set RI is shown in Table 2.
If CR ≤ 10%, the matrix is consistent and FAHP can be continued.If CR > 10%, it requires revision because the matrix is not consistent.In this paper, the root mean square method is used to carry out the consistency test.The model calculation procedure is as follows ：

2-tuple linguistic information
Professor Herrera, a Spanish scholar, put forward 2-tuple linguistic information [15]method of the Linguistic aggregation information for the first time in 2000.It can solve the problem of the loss and distortion of the language information so as to make the evaluation information more accurate.At the same time, he also proposed Time-ordered Weighted Averaging Operator(T-OWA) based on 2-tuple linguistic information in 2001.And it was successfully applied to multi attribute evaluation and decision analysis of multi granularity linguistic scales [16].
2-tuple linguistic information is the result of language evaluation with ， in which is the first K elements of the language information evaluation set S, and is the symbol conversion value with ∈[-0.5，0.5).It represents the deviation between the linguistic information set and the most appropriate linguistic phrase in the pre-defined language information set S. and are described as follows.
  [15,16,18] It is used to aggregate the linguistic evaluation information of the experts.The definition of T-OWA operator is: If is a set of 2-tuple linguistic evaluation information, and the definition of T-OWA operator is defined as follows:

The T-OWA operator
In the equation, element of vector represents the one of the first bit in the set , which is in accordance with the order of large to small.And represents the weight vector of each expert.

The definition of fuzzy operator
The definition is as follows , In the equation, , and under such a principle of at least half, most and as many as possible situation, parameter is (0,0.5)，(0.3,0.8)，(0.5,1).

Empirical analysis
The mine is located in the southwest of the Hubei Province in the central part of China, and it has general hydrogeological conditions.Additionally, OHSAS18001 has currently been utilized for the site for more than three years.As a result, it has a good reputation in the society as well as the local community.Utilizing the mine as an example, this paper evaluates and analyses the employee satisfactory of OHSAS through a fuzzy analytic hierarchy process (FAHP) method and a 2-tuple linguistic evaluation information.

The weight and consistency test
In order to ensure the validity and consistency of the evaluation model, the indicators need to be tested.Additionally, thirty Chinese senior staff with more than 5 years working experience in the mine were invited to judge the importance of the indicators in the FAHP method.In this paper, the root mean square method is used to carry out the consistency test.The calculation procedure of the first grade indicators weight is shown as follows.
According to the aforementioned formulas, calculation of first-grade indicator is obtained as  In the same way, the weight of the second grade indicators can be obtained, and the results are shown as below: ; ; ;

Semantic comments on the employee satisfaction evaluation indicator
According to the evaluation of 2-tuple linguistic information, the evaluation indicator is divided into six grades, as shown in Table 4.

The weight vector and 2-tuple linguistic information of the second grade indicator
According to the formula (3), the weight of the score is obtained as follows: ；According to the definition (3), the vector of u11 in accordance with the order from large to small is calculated as follows: ; According to the formula (1), it can be calculated as follows: ， According to the definition (3), The 2-tuple linguistic information after the aggregation of u11 is obtained as follows: (s3,-0.290);In the same way, The 2-tuple linguistic information after the aggregation of other second grade indicators can be obtained as in Table 8.According to the formula (4), the 2-tuple linguistic information after integration of the second grade indictor as follows: In the same way, the comprehensive β value and the comprehensive 2-tuple linguistic information can be obtained as shown in Table 6.
Table6.Indicator weight β value and 2-tuple linguistic information.In the same way, comprehensive 2-tuple linguistic information of first grade indicator can be calculated as follows:

First
According to comprehensive 2-tuple linguistic information of first and second grade indicators, the mine that is managed according to the occupational health and safety management system achieves a grade of "good" economical efficiency of employee satisfactory with the others of " normal" grade.But the overall employee satisfaction of the OHSAS 18001 belongs to "general" grade, which still needs to be further improved.

Conclusion
Enterprise employee satisfaction evaluation is a kind of subjective judgment, whose method of preparation of the scale is easy to cause information distortion.Additionally, the integrity of information can not be preserved in the process of language integrating.And the 2-tuple linguistic information and operator methods overcome the above shortcomings.5 indicators of OHSAS18001 employee satisfaction of humanization, effectiveness, economical efficiency, social efficiency, and environmental efficiency are given and combined with the characteristics of OHSAS18001.And the method of FAHP is used to calculate the weight of the first and second grade indicators, whose consistency is verified by the root mean square method.The reliability of the results is guaranteed.At the same time, the feasibility of the method is authenticated by the empirical study of 2-tuple linguistic information, which provides an important reference for the effective operation and strategic management of the mine OHSAS18001.
The geographical positions, management mode, and single system or multi system of different mines in China vary greatly.There are many different ways to evaluate the employee satisfaction of OHSAS1800.Thus, this method allows for necessary adjustments according to the actual situation and experience.For future work, the research in this area should be strengthened, the constructed model should be optimized, and in the selection of evaluation methods, we should consider effectively integrating 2-tuple linguistic information, projection operator and geometric weighted averaging operator to further enrich the model of employee satisfaction based on the 2-tuple linguistic information.

1 .
Multiply the elements of B by line u = 2.The nth root of the resultant product u = 3. Normalize the root mean square vector and get the feature vector W = 4. Calculate the largest eigenvalue of the judgment matrix λ = 5.Calculate CR = CI/RI=(λ-n)/(n -1)/ RI

Table 1 .
Occupational health and safety management system employee satisfaction indicators.

Table 2 .
The experts scoring table of the importance among indicators.

Table 3 .
Calculation results of first-grade indicator.