Research on Comprehensive Evaluation of Performance of

Traditional Chinese Medicine Project based on Grey Correlation

Analysis

Zijian Ren

, Shuanggui Tian

, Yong Xiao

and Ziyan Xu

School of Information Engineering, Hubei University of Chinese Medicine, Wuhan, China

School of Management, Hubei University of Chinese Medicine, Wuhan, China

Corresponding author

382217419@qq.com

XY_1015@126.com

938282571@qq.com

Keywords: Grey Correlation Analysis, Performance Management, Comprehensive Evaluation, TCM Project.

Abstract: This paper studied the main factors affecting the execution rate of Traditional Chinese Medicine (TCM)

project funds and the comprehensive evaluation result of TCM project performance by grey correlation

analysis. During the study, we called the funds evaluation rate and performance evaluation scores of the four

categories of TCM projects in 15 cities as performance evaluation data, and used them as the original data for

the research. In the study of influencing factors, the funds execution rate was used as the reference sequence,

and the project performance evaluation scores were used as the comparison sequences, in the study of the

comprehensive evaluation, the performance evaluation data of an ideal city was set as the reference sequence,

and the performance data of 15 cities were used as the comparison sequences. Then, the data of the sequences

were non-dimensionalized, to calculate the correlation coefficient and correlation degree of the comparison

sequences, and sort the correlation degree. The results indicated that the implementation of category D project

had the greatest impact on the funds evaluation rate, the comprehensive evaluation of cities D, O, E, N, B, M

and I ranked high. The comprehensive evaluation result obtained by grey correlation analysis was consistent

with the evaluation result of third-party experts, it could reflect the comprehensive situation of different cities

and projects. It is proposed that the competent department of TCM project can improve the performance

management level of TCM project from the aspects of optimizing budget allocation, improving the index

system, carrying out comprehensive performance evaluation and improving the whole process management

of TCM project.

1 INTRODUCTION

With the continuous increase of the central

government's investment in special funds for TCM

projects, government departments have increasingly

strict requirements for fund management and

performance evaluation of TCM projects. At present,

the performance evaluation of TCM projects mainly

adopts the performance report formed by the

submission of performance data by the evaluated unit,

performance self-evaluation and expert sampling on-

https://orcid.org/0000-0002-4898-6652

https://orcid.org/0000-0001-7755-7876

https://orcid.org/0000-0001-9768-037X

https://orcid.org/0000-0003-0209-7902

site investigation. This study uses grey correlation

analysis method to conduct in-depth research on

performance data, to help the TCM project

department in charge accurately grasp the overall

situation of the project performance. This study finds

the main factors to improve the execution rate of

TCM project funds, finds the weak links in the

implementation of TCM projects, puts forward

suggestions for improving the management of TCM

projects, and provides ideas for performance

comprehensive evaluation of TCM project.

348

Ren, Z., Tian, S., Xiao, Y. and Xu, Z.

Research on Comprehensive Evaluation of Performance of Traditional Chinese Medicine Project based on Grey Correlation Analysis.

DOI: 10.5220/0011344700003437

In Proceedings of the 1st International Conference on Public Management and Big Data Analysis (PMBDA 2021), pages 348-354

ISBN: 978-989-758-589-0

2 DATA SOURCES AND

RESEARCH METHODS

2.1 Data Sources

The data of this study is derived from the performance

evaluation data of a province's TCM project in the

TCM platform for National Health Insurance

Information Engineering in 2020, the data is filled in

by the project implementation unit, audited by a third-

party accounting firm, which is scientific. We sorted

out the funds execution rate and performance

evaluation scores data of four categories of projects

in 15 cities.

2.2 Research Methods

According to the grey system theory (Deng 2002),

this paper uses grey correlation analysis method to

carry out research, the specific calculation steps are

as follows.

1) To determine the reference sequence that

reflects the characteristics of the system's behavior

and the comparison sequences that affect the system's

behavior. Among them, the reference sequence is

usually denoted as X

, and the comparison sequences

are denoted as X

, X

,..., X

2) The new sequences are obtained by non-

dimensional processing on the reference sequence

and the comparison sequences.

3) To calculate the absolute difference between

the reference sequence and the comparison sequence,

the calculation formula is as follows:

△



(

𝑘

)

=|𝑋



(

𝑘

)

−𝑋



(

𝑘

)

| (1)

In the formula, △

(k) is the absolute difference

value, X

(k) is the value of the non-dimensional

reference sequence, and X

(k) is the value of the non-

dimensional comparison sequence.

4) To calculate the correlation coefficient of the

comparison sequences, the calculation formula is as

follows:

𝜉



(

𝑘

)



△



(

𝑘

)



+𝜌△



(

𝑘

)







△



(𝑘) +

𝜌△



(

𝑘

)





(2)

In the formula, 𝜉



(

𝑘

)

is the correlation

coefficient, △



(

𝑘

)



a nd △



(

𝑘

)



respectively

represent the minimum and maximum difference of

the absolute difference, and 𝜌 represents the

resolution coefficient, which is 0.5.

5) To calculate the correlation degree of the

comparison sequence and sort it, the calculation

formula is as follows:

𝑟







∑

𝜉



(

𝑘

)





, k=1,2,3,…,n (3)

𝑟



is the grey correlation degree of the comparison

sequences X

to the reference sequence X

. The closer

the value of 𝑟



is to 1, the better the correlation.

The degree of relevance is sorted by numerical value.

If 𝑟



> 𝑟



, the reference sequence X

is more similar

to the comparison sequence X

2.3 Data Analysis

The research data was processed with Microsoft

Excel 2019 and SPSS 21.0 software and analyzed for

grey correlation analysis.

3 RESULTS AND ANALYSIS

3.1 Basic Information

The performance evaluation data of this research is

the total funds execution rate of the four categories of

projects A, B, C, and D in 15 cities and the

performance evaluation scores of each project, the

evaluation score is based on a percentage system, as

shown in Table 1. From the perspective of project

funds execution rate, City C, City I and City L have

the top performance rankings, with an execution rate

of 100%. While City G, City J, City F and City K rank

lower in terms of performance, with lower funds

execution rates, they are 78.04%, 74.66%, 67.28%

and 30.56% respectively. Judging from the average

scores of the cities in the project performance

evaluation, the performance of City D, City O, City E

and City M are ranked high, with scores of 92.61,

91.63, 91.04 and 90.58 respectively, City C and City

F, City H, City A, and City K rank low in

performance, with a score of less than 85. The

rankings obtained from the two evaluation angles

have a large gap, which are not enough to reflect the

overall performance level of the cities.

Research on Comprehensive Evaluation of Performance of Traditional Chinese Medicine Project based on Grey Correlation Analysis

349

Table 1: Cities performance evaluation data.

cities

Category A

(points)

Categor y B

(points)

Category C

(points)

Category D

(points)

Average

score (points)

Funds execution

rate (%)

C 78.33 80.00 87.50 83.33 82.29 100.00

I 85.00 83.33 100.00 80.00 87.08 100.00

L 91.00 75.00 85.00 90.00 85.25 100.00

N 79.50 86.00 92.50 97.50 88.88 99.45

A 59.50 81.67 81.50 100.00 80.67 99.19

D 89.20 93.75 100.00 87.50 92.61 98.43

B 85.88 80.00 100.00 90.00 88.97 98.20

M 87.80 87.00 92.50 95.00 90.58 96.33

E 85.00 89.17 100.00 90.00 91.04 95.61

H 86.00 70.00 75.84 93.75 81.40 93.44

O 82.78 83.75 100.00 100.00 91.63 90.53

G 86.88 81.67 91.25 90.00 87.45 78.04

J 97.50 85.00 83.33 89.29 88.78 74.66

F 71.67 80.00 85.00 90.00 81.67 67.28

K 85.00 80.00 85.00 70.00 80.00 30.56

3.2 Grey Correlation Analysis of

Project Funds Execution Rate and

Performance Evaluation Scores

According to the grey system theory, 15 cities are

regarded as a grey system, and using grey correlation

analysis method to calculate the correlation between

the project funds execution rate and the performance

evaluation scores (Liu et al. 2021). According to the

calculation steps, seting the project funds execution

rate as the reference sequence X

, and the performance

evaluation scores of the four categories of projects A,

B, C, and D as the comparison sequences X

(i=1,2,3,4). The initial value method is used to non-

dimensionally process the data of each sequences, and

the results are shown in Table 2. Calculating the

absolute difference △

(k) of each performance

evaluation score according to the data in Table 2, the

results are shown in Table 3. It can be seen from the

results in Table 3 that △

(k)

min

is 0 and △

(k)

max

0.5444. Further according to the formulas (2) and (3),

the correlation coefficient and correlation degree of

the performance evaluation scores to the funds

execution rate are calculated, as shown in Table 4.

Table 2: Dimensionless processing of performance evaluation data.

cities Category A Category B Category C Category D

Funds execution rate

A 0.5950 0.8167 0.8150 1.0000 0.9919

B 0.8588 0.8000 1.0000 0.9000 0.9820

C 0.7833 0.8000 0.8750 0.8333 1.0000

D 0.8920 0.9375 1.0000 0.8750 0.9843

E 0.8500 0.8917 1.0000 0.9000 0.9561

F 0.7167 0.8000 0.8500 0.9000 0.6728

G 0.8688 0.8167 0.9125 0.9000 0.7804

H 0.8600 0.7000 0.7584 0.9375 0.9344

I 0.8500 0.8333 1.0000 0.8000 1.0000

J 0.9750 0.8500 0.8333 0.8929 0.7466

K 0.8500 0.8000 0.8500 0.7000 0.3056

L 0.9100 0.7500 0.8500 0.9000 1.0000

M 0.8780 0.8700 0.9250 0.9500 0.9633

N 0.7950 0.8600 0.9250 0.9750 0.9945

O 0.8278 0.8375 1.0000 1.0000 0.9053

Ideal 1.0000 1.0000 1.0000 1.0000 1.0000

PMBDA 2021 - International Conference on Public Management and Big Data Analysis

350

Table 3: Absolute difference table of grey correlation

analysis between funds execution rate and performance

evaluation scores.

cities

Category

Funds

executio

n rate

A 0.4050 0.1833 0.1850 0.0000 0.0081

B 0.1412 0.2000 0.0000 0.1000 0.0180

C 0.2167 0.2000 0.1250 0.1667 0.0000

D 0.1080 0.0625 0.0000 0.1250 0.0157

E 0.1500 0.1083 0.0000 0.1000 0.0439

F 0.2833 0.2000 0.1500 0.1000 0.3272

G 0.1312 0.1833 0.0875 0.1000 0.2196

H 0.1400 0.3000 0.2416 0.0625 0.0656

I 0.1500 0.1667 0.0000 0.2000 0.0000

J 0.0250 0.1500 0.1667 0.1071 0.2534

K 0.1500 0.2000 0.1500 0.3000 0.6944

L 0.0900 0.2500 0.1500 0.1000 0.0000

M 0.1220 0.1300 0.0750 0.0500 0.0367

N 0.2050 0.1400 0.0750 0.0250 0.0055

O 0.1722 0.1625 0.0000 0.0000 0.0947

Research on Comprehensive Evaluation of Performance of Traditional Chinese Medicine Project based on Grey Correlation Analysis

351

Table 6: Correlation coefficient and correlation degree of performance evaluation data.

cities Category A Category B Category C Category D

Funds

execution rate

Correlation

degree

D 0.7627 0.8474 1.0000 0.7353 0.9567 0.8604

O 0.6685 0.6812 1.0000 1.0000 0.7856 0.8271

E 0.6983 0.7622 1.0000 0.7764 0.8878 0.8249

N 0.6288 0.7126 0.8224 0.9328 0.9845 0.8162

B 0.7109 0.6345 1.0000 0.7764 0.9506 0.8145

M 0.7400 0.7276 0.8224 0.8741 0.9044 0.8137

I 0.6983 0.6756 1.0000 0.6345 1.0000 0.8017

L 0.7941 0.5814 0.6983 0.7764 1.0000 0.7700

A 0.4616 0.6545 0.6524 1.0000 0.9772 0.7491

C 0.6157 0.6345 0.7353 0.6756 1.0000 0.7322

J 0.9328 0.6983 0.6756 0.7643 0.5781 0.7298

G 0.7258 0.6545 0.7987 0.7764 0.6126 0.7136

H 0.7126 0.5365 0.5897 0.8474 0.8410 0.7054

F 0.5507 0.6345 0.6983 0.7764 0.5149 0.6349

K 0.6983 0.6345 0.6983 0.5365 0.3333 0.5802

According to the principle of grey correlation

analysis, the higher the correlation degree of a city,

the closer it is to the performance evaluation result of

the ideal city, and the higher its comprehensive

evaluation level will be. According to the results in

Table 6, the comprehensive evaluation of project

performance of the 15 cities is ranked as City D＞

City O＞City E＞City N＞City B＞City M＞City I

＞City L＞City A＞City C＞City J＞City G＞City

H＞City F＞City K.

4 DISCUSSIONS

4.1 Factors Influencing Project Funds

Execution Rate

According to the results, the order of the degree of

influence of the performance evaluation scores of

each project on the funds execution rate is: Category

D > Category C > Category B > Category A. The four

categories of projects are the novel coronavirus

Pneumonia prevention and treatment capacity

building of TCM, TCM culture and industry, TCM

talent training, and TCM medical service capacity

building. Therefore, in the process of implementing

TCM projects, cities should focus on improving the

performance evaluation score of category D project.

Specific measures include improving the

infrastructure of relevant business departments and

cultivating relevant talents. The correlation degree of

category C is 0.7382, which has a higher correlation

degree with the funds execution rate. The category C

project includes the investigation of citizens' TCM

health culture literacy and the promotion of TCM

health culture. Cities need to improve the quality of

the questionnaire, enrich the survey methods, and

improve the professionalism of the investigators, at

the same time, actively carry out the cultural

dissemination and publicity activities of TCM, to

improve the performance evaluation score of

category C project.

4.2 Comprehensive Performance

Evaluation

The results show that City D ranks first

comprehensively, and the correlation coefficients of

all indicators exceed 0.7, but the Category A and

Category D projects he undertakes still need to be

strengthened. City O, City E, City N, City B, City M,

City I, City L, City A, and City C have a high

correlation coefficient in the funds execution rate.

PMBDA 2021 - International Conference on Public Management and Big Data Analysis

352

Therefore, they should increase the performance

evaluation scores of weak projects to improve the

overall ranking. The lower-ranked cities J, G, F, and

K have a low correlation coefficient in the funds

execution rate. Therefore, they should regulate the

use of funds to increase the execution rate, in order to,

improve the overall ranking. City H has the lowest

correlation coefficient in Category B and Category C

projects, so, it is necessary to focus on rectification

and reform of these two categories of projects, in

order to improve the comprehensive ranking.

5 SUGGESTIONS

5.1 Optimizing Budget Allocation, and

Improving the Index System

A reasonable budget allocation and a comprehensive

performance evaluation index system are the basis for

improving the funds execution rate and project

performance evaluation scores, and are the key

factors to improve the quality of performance

evaluation. In terms of budget allocation, the

department in charge of TCM projects should strictly

follow the principles of overall planning, fairness and

justice (Huo 2021), and allocate project budgets in

accordance with areas and proportions. Local

financial departments and business management

departments need to strengthen communication in the

process of budget formulation (Wu, Tian & Shen

2019), do a good job of investigation and research in

the early stage of project implementation. In terms of

the performance evaluation index system, the basic

principles to be followed by the department in charge

of TCM projects are: combination of qualitative and

quantitative, combination of theory and practice,

combination of completeness and simplicity, and

combination of objectivity and orientation. Through

the extensive collection of opinions from experts and

professional staff, a performance evaluation index

system with TCM characteristics and in line with the

goals of the TCM project is constructed.

5.2 Carrying out Comprehensive

Evaluation of the Performance of

TCM Projects

At present, TCM projects performance evaluation

often uses single indicators such as project

performance evaluation score or funds execution rate

to evaluate the project implementation unit, which is

not enough to reflect the overall level of the

implementation unit and the overall implementation

of the project. Therefore, the competent department

of TCM projects should actively use grey correlation

analysis method, analytic hierarchy process, indirect

evaluation method and other scientific evaluation

methods when performing performance evaluation.

Scientific evaluation results can mobilize the

initiative of the competent department and project

undertaking units (Huang & Xiao 2017), which is

conducive to to comprehensively grasp the

implementation of the project, find the weak links,

and provide a basis for the competent authority to

make reasonable decisions on the project.

5.3 Improving the Whole Process

Management of TCM Projects

The competent department of TCM projects should

improve management system and realize the whole

process management from project application,

establishment, implementation, interim inspection,

acceptance and performance evaluation. First,

establishing a database of TCM projects, carrying out

ex ante performance evaluation, realizing "project

planning first and fund allocation later". Second,

forming a standardized and real-time project

management and supervision system, dynamically

grasping project progress (Xue 2021), in order to,

improve performance management. What's more

important, the competent department of TCM

projects should actively use information technology,

and establish a database covering the entire process

of budget declaration, review, execution and

performance evaluation (Li & Xie 2020). TCM

project performance management information system

should be constructed to realize the visualization and

informatization of project implementation process

data, carry out monitoring, early warning and

accurate evaluation of project performance operation.

It can also support data collection, performance

evaluation and scientific research for TCM projects.

In the end, the performance evaluation feedback

mechanism should be established (Chen, Leng & Jin

2016). The performance evaluation results should be

linked to the budget preparation, implementing an

accountability system for units to ensure the

standardization and rationality of project

implementation. As a safeguard measure of

performance management, it is necessary to establish

a team of performance management talents to ensure

the completion of various work with high quality.

Research on Comprehensive Evaluation of Performance of Traditional Chinese Medicine Project based on Grey Correlation Analysis

353

6 CONCLUSION

This study uses grey correlation analysis method to

combine the performance evaluation score and the

funds execution rate two major indicators to

comprehensively evaluate the performance

evaluation data of TCM projects in 15 cities, and find

important factors that affect the funds execution rate

and comprehensive ranking. On the other hand, due

to the limitation of report data, this study does not

include other indicators such as the number of

completed performance indicators, provinces and

years into the study, and the research conclusion has

certain limitations. The follow-up research will

further increase relevant evaluation indicators and

conduct multi-dimensional analysis of performance

evaluation data.

ACKNOWLEDGEMENTS

Research on Performance Evaluation of Traditional

Chinese Medicine Projects in Hubei Province in

2021(Project No: HBZY-2021-Z09).

REFERENCES

Chen Zhihui, Leng Xifen & Jin Yimin. (2016). Discussion

on the problems and countermeasures of performance

management of agricultural scientific research projects

(z2), 57-58.

Deng Julong. (2002). Basis of grey theory. Wuhan:

Huazhong University of Science and Technology Press.

Huang Yao & Xiao Yong. (2017). Comprehensive

evaluation of the implementation of traditional Chinese

medicine projects based on the Kernel_PCA algorithm.

China Health Statistics (04), 681-683+687. doi:

Huo Shenglu. (2021). Research on Performance Evaluation

of Provincial Sports Lottery Public Welfare Funds

(Doctoral Dissertation, Shanghai Institute of Physical

Education).

https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=

CDFDLAST2021&filename=1021655062.nh

Li Wenbin & Xie Xin. (2020). Big Data Technology and

Quality Improvement of Budget Performance

Management. Learning Forum (04), 38-45.

doi:10.16133/j.cnki.xxlt.2020.04.007.

Generate Citation

Liu Meiru, Zhang Xianmei, Zhang Quan, Zheng Lei, Wu

Hemin, Dai Jin... & Liu Lifeng. (2021). Grey

Correlation Analysis and Comprehensive Evaluation of

the Yield-related Traits of 20 Sesame Cultivars.

Shandong Agricultural Sciences (07), 19-26.

doi:10.14083/j.issn.1001-4942.2021.07.004.

Wu Xiaohua, Tian Shuanggui & Shen Shaowu. (2019).

Research on Informatization of Project Budget

Management of Traditional Chinese Medicine. Herald

of Traditional Chinese Medicine (19), 20-24.

doi:10.13862/j.cnki.cn43-1446/r.2019.19.006.

Xue Pengren. (2021). Research on the Performance

Evaluation of Medical and Health Financial

Expenditure in Anhui Province (Master's thesis, Jiangxi

University of Finance and Economics).

https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=

CMFD202102&filename=1021612899.nh

PMBDA 2021 - International Conference on Public Management and Big Data Analysis

354